CN113473487B

CN113473487B - Method, device, equipment and storage medium for optimizing store construction in base station area

Info

Publication number: CN113473487B
Application number: CN202010242948.3A
Authority: CN
Inventors: 霍立; 尹零计; 陈诚
Original assignee: China Mobile Communications Group Co Ltd; China Mobile Group Guizhou Co Ltd
Current assignee: China Mobile Communications Group Co Ltd; China Mobile Group Guizhou Co Ltd
Priority date: 2020-03-31
Filing date: 2020-03-31
Publication date: 2022-09-27
Anticipated expiration: 2040-03-31
Also published as: CN113473487A

Abstract

An embodiment of the present specification provides a method for optimizing construction of stores in a base station area, including: determining a first service capability value according to a first service parameter value of a target base station region and each base station region of the same type in a first geographical range; determining a service capability standard value according to a target base station region and a first service capability value of each base station region of the same type in a first geographical range; if the first service capability value is smaller than the service capability standard value and the number of stores is smaller than the preset number, determining a second service capability value according to a second service parameter value of each base station area of the same type in the target base station area and a second geographic range; and determining a site selection score value according to the second service capability value, the base station position and the store position, and determining a construction optimization scheme according to the site selection score value and a preset income value. The technical scheme of the embodiment of the invention can efficiently and accurately provide the construction optimization scheme of the store in the base station area without depending on manual data acquisition and without making a scheme according to manual experience.

Description

Method, device, equipment and storage medium for optimizing store construction in base station area

Technical Field

The document relates to the technical field of big data, in particular to a construction optimization method, a device, equipment and a storage medium for stores in a base station area.

Background

Stores are the primary route for commercial marketing, with the majority of goods sold in the stores. How to build and optimize stores in a target area, so that the sales capacity and market share of the stores are improved, the production and business cost is reduced, and the method is an important subject of market research. In the prior art, how to evaluate the construction optimization of stores in a target area depends on manual data acquisition and a construction optimization scheme is formulated according to manual experience, so that the efficiency is low and the accuracy is low. Therefore, a technical solution is needed to solve the problem that it is difficult to efficiently and accurately provide an optimization solution for store construction in a target area.

Disclosure of Invention

An object of one embodiment of the present specification is to provide a method, an apparatus, a device, and a storage medium for optimizing construction of stores in a base station area, so as to solve the problem that it is difficult to efficiently and accurately provide a scheme for optimizing construction of stores in a target area.

To solve the above technical problem, one embodiment of the present specification is implemented as follows:

in a first aspect, an embodiment of the present specification provides a method for optimizing the construction of stores in a base station area, including:

determining a first service capability value of an store in the target base station region according to the value of the first service parameter of the target base station region and the value of the first service parameter of each base station region of the same type as the target base station region in the first geographical range in which the target base station region is located;

determining a service capability standard value of an store in the target base station area according to the first service capability value of the store in the target base station area and the first service capability value of stores in each base station area of the same type as the target base station area in the first geographical range;

if the first service capability value of the stores in the target base station area is smaller than the service capability standard value of the stores in the target base station area, and the number of the stores in the target base station area is smaller than the preset number of stores, determining a second service capability value of the stores in the target base station area according to the value of a second service parameter of the target base station area and the values of the second service parameters of all base station areas of the same type as the target base station area in a second geographical range in which the target base station area is located;

and determining the site selection score value of the target base station area according to the second service capability value of the store in the target base station area, the position of the base station in the target base station area and the positions of all stores in the target base station area, and determining the construction optimization scheme of the stores in the target base station area according to the site selection score value of the target base station area and the preset income value corresponding to the target base station area.

In a second aspect, another embodiment of the present specification provides an apparatus for optimizing construction of stores in a base station area, including:

the first service capability value determining module is used for determining a first service capability value of an store in the target base station area according to the value of the first service parameter of the target base station area and the value of the first service parameter of each base station area of the same type as the target base station area in the first geographical range in which the target base station area is located;

the service capability standard value determining module is used for determining a service capability standard value of an store in the target base station area according to a first service capability value of the store in the target base station area and a first service capability value of stores in each base station area of the same type as the target base station area in a first geographical range;

the second service capability value determining module is used for determining a second service capability value of an store in the target base station area according to the value of a second service parameter of the target base station area and the values of the second service parameters of base station areas in the same type as the target base station area in a second geographic range in which the target base station area is located if the first service capability value of the store in the target base station area is smaller than the service capability standard value of the store in the target base station area and the number of the stores in the target base station area is smaller than the preset number of stores;

and the construction optimization scheme determining module is used for determining the site selection score value of the target base station region according to the second service capability value of the store in the target base station region, the position of the base station in the target base station region and the positions of all stores in the target base station region, and determining the construction optimization scheme of the store in the target base station region according to the site selection score value of the target base station region and the preset income value corresponding to the target base station region.

In a third aspect, a further embodiment of the present specification provides a construction optimization apparatus for stores in a base station area, including: a memory, a processor and computer executable instructions stored on the memory and executable on the processor, the computer executable instructions when executed by the processor implementing a method of construction optimization of stores within a base station area as described in the first aspect above.

In a fourth aspect, a further embodiment of the present specification provides a computer-readable storage medium for storing computer-executable instructions which, when executed by a processor, implement the method for optimizing construction of stores in a base station area as described in the first aspect above.

According to the technical scheme of the embodiment of the invention, firstly, a first service capability value of an store in a target base station area is determined according to values of first service parameters of each base station area and the target base station area of the same type as the target base station area in a first geographical range in which the target base station area is located; then, determining a service capability standard value of an in-store in the target base station area according to first service capability values of in-store in each base station area and in-store in the target base station area which are in the same type as the target base station area in the first geographical range; then, if the first service capacity value of the store in the target base station area is smaller than the service capacity standard value and the number of the stores in the target base station area is smaller than the preset number of stores, determining a second service capacity value of the store in the target base station area according to the values of second service parameters of each base station area and the target base station area which are in the same type as the target base station area in a second geographic range in which the target base station area is located; and finally, determining the site selection score value of the target base station area according to the second service capability value of the store in the target base station area, the position of the base station in the target base station area and the positions of all stores in the target base station area, and determining the construction optimization scheme of the store in the target base station area according to the site selection score value of the target base station area and the preset income value corresponding to the target base station area. According to the embodiment of the invention, the first service capability value and the standard service capability value of the stores in the target base station area can be determined, whether the stores in the target base station area need to be optimized is determined according to the comparison result of the first service capability value and the standard service capability value, if the stores in the target base station area need to be optimized, the second service capability value is determined, the site selection score value of the target base station area is determined according to the second service capability value, the base station position and the store position, and the construction optimization scheme of the stores in the target base station area is determined according to the comparison result of the site selection score value and the preset profit value.

Drawings

In order to more clearly illustrate the technical solutions in one or more embodiments of the present specification, the drawings used in the embodiments or the description of the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present specification, and for those skilled in the art, other drawings may be obtained according to these drawings without creative efforts.

Fig. 1 is a schematic flow chart of a method for optimizing the construction of stores in a base station area according to an embodiment of the present disclosure;

fig. 2 is a schematic flow chart of a method for optimizing the construction of stores in a base station area according to another embodiment of the present disclosure;

FIG. 3 is a schematic diagram of store classifications provided by one embodiment of the present specification;

fig. 4 is a schematic diagram of an application scenario of base station area division according to an embodiment of the present disclosure;

fig. 5 is a schematic block diagram of a construction optimization apparatus for shops in a base station area according to an embodiment of the present invention;

fig. 6 is a schematic structural diagram of a construction optimization device for stores in a base station area according to an embodiment of the present disclosure.

Detailed Description

In order to make those skilled in the art better understand the technical solutions in one or more embodiments of the present disclosure, the technical solutions in one or more embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in one or more embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from one or more of the embodiments described herein without making any inventive step, shall fall within the scope of protection of this document.

The embodiment of the invention provides a construction optimization method, a device, equipment and a storage medium for stores in a base station area. The construction optimization method for the shops in the base station area can be applied to electronic equipment, and the electronic equipment provided by the embodiment of the invention comprises but is not limited to a mobile phone, a tablet computer, a computer, wearable equipment, an optical modem and the like.

Fig. 1 is a schematic flow chart of a method for optimizing the construction of stores in a base station area according to an embodiment of the present disclosure. Referring to fig. 1, the method for optimizing the construction of stores in a base station area includes steps S110, S120, S130, and S140. A method for optimizing the construction of stores in the base station area in the exemplary embodiment of fig. 1 will be described in detail below.

In step S110, a first service capability value of an store in the target base station region is determined according to the value of the first service parameter of the target base station region and the values of the first service parameters of base station regions in the same type as the target base station region in the first geographical range in which the target base station region is located.

In the exemplary embodiment, the province is originally divided into four levels of regions, namely province, state, county and grid from large to small. The invention further divides the grid area into a plurality of base station areas on the basis of four-level area division. Each base station area comprises one or more base station sectors, and the base station area is smaller than the grid area, and generally, the base station area in an urban area is a community or a cell; the base station area in the rural area is one or more villages or a village town. At least one base station is included in the base station area, generally, the center position of each base station area is a certain base station, and the floating population in the base station area exceeds 1000 people. The base station area may be a circular area, a square area, or an area with other preset shapes, and the present invention is not limited to this. The different base station areas do not overlap each other. There may or may not be one or more stores within the base station area. Each store must be located within a certain base station area. The location of the base station area is determined based on the base station location.

It should be noted that, in the exemplary embodiment, the construction optimization device of the store in the base station area determines population-related parameters such as the number of service users, the number of area resident population, the number of total area users, and the like in the base station area through data collected by the base station in the center of the base station area when people near the base station perform communication activities, and the population-related parameters are used in subsequent steps.

In an exemplary embodiment, the base station areas are classified into urban and rural types according to the base station location of the center of the base station area. The urban area types are divided into core urban area types and general urban area types. The core urban area refers to a city with population and other parameters exceeding a preset threshold, for example, provincial cities of each province generally belong to the core urban area; the general urban area refers to a city with population parameters lower than a preset threshold value, for example, a three-line small city with a small population belongs to the general urban area. It should be noted that the core urban area is a single city, not a busy section of the city, but a general urban area is a single city, not a cooler section of the city.

In an example embodiment, the first geographic scope may be a province or other customized geographic scope, such as a customized provinces or a customized city or a preset area.

In the exemplary embodiment, it is assumed that the base station area 1 of the core urban area type is selected as the target base station area, and the first geographical range is province, and each base station area of the same type as the target base station area in the first geographical range in which the target base station area is located is each base station area belonging to the core urban area type in the province a in which the base station area 1 is located.

In an example embodiment, the determining, by the first service parameter including a plurality of first preset parameters, a first service capability value of an store in the target base station area according to a value of the first service parameter of the target base station area and values of the first service parameter of base station areas of the same type as the target base station area in a first geographical range in which the target base station area is located includes: for each first preset parameter, counting the value of the first preset parameter of the target base station area and the value of the first preset parameter of each base station area of the same type as the target base station area, and determining the maximum value, the minimum value and the median value corresponding to the first preset parameter; determining the capacity value of the target base station area corresponding to the first preset parameter according to the value of the first preset parameter of the target base station area, the maximum value, the minimum value and the median value corresponding to the first preset parameter, the preset weight and the direction coefficient corresponding to the first preset parameter; and summing the capability values of the target base station area corresponding to the first preset parameters to obtain a first service capability value of an store in the target base station area.

In an example embodiment, the first traffic parameter includes a plurality of first preset parameters, and the plurality of first preset parameters include, but are not limited to, net increase share, new increase share, market share, store share, number of service users, area resident population, total number of area users, area GDP, store average reward. The first preset parameters are preset big data analysis dimensions. The weight of each first preset parameter is defined by combining the characteristics of products sold by stores in the base station area and by an expert analysis method. Each first predetermined parameter also has a predetermined directional coefficient, as shown with reference to table 1.

TABLE 1

Serial number	First preset parameter	Coefficient of direction	Direction value	Description of the invention
					1	Net increase of the fraction	Tr ₍₁₎	-1	Negative coefficient
2	New share of	Tr ₍₂₎	-1	Negative coefficient
					3	Market share	Tr ₍₃₎	-1	Negative coefficient
4	Store quota	Tr ₍₄₎	-1	Coefficient of negative going
					5	Number of service subscribers	Tr ₍₅₎	1	Coefficient of forward direction
6	Area of area	Tr ₍₆₎	1	Coefficient of forward direction
					7	Number of regional resident population	Tr ₍₇₎	1	Coefficient of forward direction
8	Total number of regional users	Tr ₍₈₎	1	Coefficient of forward direction
					9	Region GDP	Tr ₍₉₎	1	Coefficient of forward direction
10	Average reward of store	Tr ₍₁₀₎	1	Coefficient of forward direction

In an example embodiment, base station areas of the same type as the target base station area within the first geographical area in which the target base station area is located do not include the target base station area. For example, assuming that the first geographical area is province a, the target base station area is base station area 5, the type of base station area 5 is rural type, and there are 5 total base station areas of rural type included in province a, which are base station area 1, base station area 2, base station area 5, base station area 7, and base station area 8, respectively, each base station area in province a where base station area 5 is located is base station area 1, base station area 2, base station area 7, and base station area 8, which are of the same type as base station area 5.

Further, in an example embodiment, for each first preset parameter, the value of the first preset parameter of the target base station region and the value of the first preset parameter of each base station region of the same type as the target base station region are counted, and a maximum value, a minimum value, and a median corresponding to the first preset parameter are determined. For example, assuming that the first geographic range is a province a, the target base station area is a base station area 5, the type of the base station area 5 is a rural type, 5 base station areas of rural types included in the province a are respectively a base station area 1, a base station area 2, a base station area 5, a base station area 7 and a base station area 8, and for a certain first preset parameter, for example, the number of area resident population, the number of base station area 1 is 1050 people, the number of base station area 2 is 970 people, the number of base station area 5 is 1350 people, the number of base station area 7 is 990 people, and the number of base station area 8 is 890 people, the number of area resident population of the base station area 1, the base station area 2, the base station area 7 and the base station area 8 in the same type as the base station area 5 in the province a is counted, and the maximum value of the area resident population of the area is 1350, the minimum value is 890, and the median is 990.

In an example embodiment, a capability value of a target base station region corresponding to a first preset parameter is determined according to the value of the first preset parameter of the target base station region, a maximum value, a minimum value and a median value corresponding to the first preset parameter, a preset weight and a direction coefficient corresponding to the first preset parameter; and summing the capability values of the target base station area corresponding to the first preset parameters to obtain a first service capability value of an store in the target base station area. Specifically, the following formula can be referred to:

when F is present _n >＝F _{n (median)} When is, P _n ＝W _{n (weight)} ×50+[F _n -F _{n (median)} ]/[F _{n (maximum number)} -F _{n (median)} ]×W _{n (weight)} ×50；

When F is present _n <F _{n (median)} When P is present _n ＝W _{n (weight)} ×50-[F _{n (median)} -F _n ]/[F _{n (median)} -F _{n (minimum number)} ]×W _{n (weight)} ×50。

n is the serial number of a first preset parameter such as the number of service users, the area, the number of area resident population, the total number of area users, the area GDP and the like;

F _n in the target base station area, the value of a first predetermined parameter with the sequence number n, e.g. F ₁ Is the value of the net gain of the target base station area, F ₅ A value of the number of service users for a target base station area;

F _{n (median)} Aiming at a first preset parameter with the sequence number n, the median of the value of the first preset parameter of the target base station area and the value of the first preset parameter of each base station area in the same type as the target base station area in a first geographical range;

F _{n (maximum number)} The maximum number of the values of the first preset parameter of the target base station area and the first preset parameter of each base station area in the same type as the target base station area in a first geographical range is determined according to the first preset parameter with the serial number of n;

F _{n (minimum number)} Aiming at a first preset parameter with the serial number of n, the minimum number of the value of the first preset parameter of a target base station area and the value of the first preset parameter of each base station area with the same type as the target base station area in a first geographical range;

W _{n (weight)} Defining a first preset parameter with the sequence number n by an expert analysis methodThe weight value of (2);

P _n aiming at a first preset parameter with the serial number n, the target base station area corresponds to the capacity value of the first preset parameter;

T _r(n) the deviation coefficient of a first preset parameter with the sequence number n;

P _m a first business capability value of a store within the target base station area.

In step S120, a service capability standard value of an store in the target base station area is determined according to the first service capability value of the store in the target base station area and the first service capability values of stores in each base station area of the same type as the target base station area in the first geographical range.

In an example embodiment, determining the standard value of the service capability of the stores in the target base station area according to the first service capability value of the store in the target base station area and the first service capability value of the stores in each base station area of the same type as the target base station area in the first geographical range comprises: counting a first service capability value of an store in the target base station area and first service capability values of stores in base station areas of the same type as the target base station area in a first geographical range to obtain a median of the first service capability values; and determining the median value of the first service capability value as a service capability standard value of the store in the target base station area.

In an example embodiment, stores within each base station area of the same type within the first geographic area as the target base station area do not include the target base station area. Suppose that the target base station area is base station area 3, and the first service capability value of the store in base station area 3 is P ₃ The base station areas in the same type as the target base station area in the first geographical range are respectively a base station area 1 and a base station area 5, and the first service capability values are respectively P ₁ And P ₅ And P is ₁ >P ₅ >P ₃ Then a first traffic capacity value P for base station area 3 ₃ And a first traffic capacity value P for a base station area 1 of the same type as the target base station area within a first geographical range ₁ And a first service capability value P of base station area 5 ₅ Making statistics to obtain first service capabilityMedian of the values P ₅ A 1 is to P ₅ A standard value of service capability for stores within the base station area 3 is determined.

It is noted that, in the exemplary embodiment, the service capability standard values of the stores in the target base station area are the same regardless of which base station area is selected as the target base station area among the base station areas of the same type in the first geographical range. For example, base station areas of rural type within the first geographical area are base station area 1, base station area 3, and base station area 5, and the standard value of the service capability of the store within the target base station area is the same regardless of whether the target base station area is base station area 1, base station area 3, or base station area 5.

In step S130, if the first service capability value of the store in the target base station area is smaller than the service capability standard value of the store in the target base station area, and the number of the stores in the target base station area is smaller than the preset number of stores, the second service capability value of the store in the target base station area is determined according to the value of the second service parameter of the target base station area and the values of the second service parameters of each base station area of the same type as the target base station area in the second geographic range where the target base station area is located.

In an example embodiment, if the first service capability value of the store in the target base station area is smaller than the service capability standard value of the store in the target base station area, which indicates that the service capability of the store in the target base station area is lower than the average level in the same type of base station area in the first geographical range, the store in the target base station area needs to be optimized for construction.

In an example embodiment, if the first service capability value of the store in the target base station area is smaller than the service capability standard value of the store in the target base station area, and the number of stores in the target base station area is smaller than the preset number of stores, it is indicated that the number of stores in the target base station area is small, the stores in the target base station area need to be added, and in order to determine what type of store is added in the target base station area, the second service capability value of the store in the target base station area needs to be calculated.

In an example embodiment, the preset number of stores may be an average value of the number of stores in the target base station area and the number of stores in each base station area of the same type as the target base station area in the first geographical range, may be a median value of the number of stores in the target base station area and the number of stores in each base station area of the same type as the target base station area in the first geographical range, or may be a numerical value summarized according to manual experience, which is not particularly limited in the present invention.

In an example embodiment, the second geographic scope may be a city, a county, or a customized geographic scope, such as customized cities, customized villages, or other predetermined areas. It is noted that the second geographical area is smaller than the first geographical area and all base station areas within the second geographical area are of the same type. For example, the second geographic area is a city a, and the city a is a core urban area, and then the base station areas in the city a are all of the core urban area type. The target base station area is located in the city A, so the type of the target base station area is a core urban area type, and each base station area in the city A, which is the same as the target base station area, is the base station area except the target base station area in the city A.

In an example embodiment, the determining, by the second service parameter including a plurality of second preset parameters, a second service capability value of an store in the target base station area according to the value of the second service parameter of the target base station area and the values of the second service parameter of base station areas in a second geographical range in which the target base station area is located, the type of which is the same as that of the target base station area, includes: for each second preset parameter, counting the value of the second preset parameter of the target base station area and the value of the second preset parameter of each base station area of the same type as the target base station area, and determining the maximum value, the minimum value and the median value corresponding to the second preset parameter; determining a capacity value of the target base station area corresponding to the second preset parameter according to the value of the second preset parameter of the target base station area, the maximum value, the minimum value and the median value corresponding to the second preset parameter, the preset weight and the direction coefficient corresponding to the second preset parameter; and summing the capacity values of the target base station area corresponding to the second preset parameters to obtain a second service capacity value of the store in the target base station area.

In an example embodiment, the second service parameter includes a plurality of second preset parameters, and the plurality of second preset parameters include, but are not limited to, a base station pedestrian volume, a port number, a station number, an area resident population number, a total number of area users, and an area GDP. The second preset parameters are preset big data analysis dimensions. And the weight of each second preset parameter is defined by combining the second preset parameters with the characteristics of the products sold by the stores in the base station area and by an expert analysis method. Each second preset parameter also has a preset directional coefficient.

In an example embodiment, base station areas of the same type as the target base station area within the second geographical area in which the target base station area is located, do not include the target base station area. For example, if the second geographic area is a city a, the target base station area is a base station area 5, the type of the base station area 5 is a core urban area type, all the base station areas included in the city a are core urban area types, and there are 5 base station areas, which are respectively a base station area 1, a base station area 2, a base station area 5, a base station area 7, and a base station area 8, then each base station area in the city a where the base station area 5 is located and which is of the same type as the base station area 5 is a base station area 1, a base station area 2, a base station area 7, and a base station area 8.

Further, in the example embodiment, for each second preset parameter, the value of the second preset parameter of the target base station region and the values of the second preset parameters of base station regions of the same type as the target base station region are counted, and a maximum value, a minimum value, and a median value corresponding to the second preset parameter are determined. For example, assuming that the second geographic range is a city a, the target base station area is a base station area 5, the type of the base station area 5 is a core city type, all the base station areas included in the city a are core city types, there are 5 base station areas, which are respectively a base station area 1, a base station area 2, a base station area 5, a base station area 7 and a base station area 8, and for a second preset parameter, for example, the number of stations of the base station area 1 is 6, the number of base station areas 2 is 4, the number of base station areas 5 is 10, the number of base station areas 7 is 2, and the number of base station areas 8 is 3, the number of stations of the base station areas 1, base station areas 2, base station areas 7 and base station areas 8 in the same type as the base station area 5 in the province a and the province a is counted, and the maximum value, the minimum value of the number of the stations is determined to be 10, the minimum value is 2, and the median is 4.

In an example embodiment, a capability value of the target base station area corresponding to the second preset parameter is determined according to the value of the second preset parameter of the target base station area, the maximum value, the minimum value and the median value corresponding to the second preset parameter, the preset weight and the direction coefficient corresponding to the second preset parameter; and summing the capacity values of the target base station area corresponding to the second preset parameters to obtain a second service capacity value of the store in the target base station area. Specifically, the following formula can be referred to:

when B is present _n >＝B _{n (median)} When, C _n ＝W _{n (weight)} ×50+[B _n -B _{n (median)} ]/[B _{n (maximum number)} -B _{n (median)} ]×W _{n (weight)} ×50；

When B is present _n <B _{n (median)} When, C _n ＝W _{n (weight)} ×50-[B _{n (median)} -B _n ]/[B _{n (median)} -B _{n (minimum number)} ]×W _{n (weight)} ×50。

n is the serial number of second preset parameters such as regional pedestrian flow, port number, station number, regional area, regional resident population number, regional total user number, regional GDP and the like of the base station;

B _n in the target base station area, the value of a second predetermined parameter with the sequence number n, e.g. B ₁ Value of base station area traffic, B, for target base station area ₅ A value of the area resident population of the target base station area;

B _{n (median)} Aiming at a first preset parameter with the sequence number n, the value of a second preset parameter of a target base station area is the same as that of the target base station area in a second geographical rangeThe median of the values of the second preset parameters of each base station area of the type;

B _{n (maximum number)} Aiming at a second preset parameter with the sequence number n, the maximum number of the values of the second preset parameter of the target base station area and the second preset parameter of each base station area in the same type as the target base station area in a second geographical range;

B _{n (minimum number)} Aiming at a second preset parameter with the sequence number n, the minimum number of the value of the second preset parameter of the target base station area and the value of the second preset parameter of each base station area in the same type as the target base station area in a second geographic range;

W _{n (weight)} Aiming at a second preset parameter with the sequence number n, defining a weighted value by an expert analysis method;

C _n aiming at a second preset parameter with the sequence number n, the target base station area corresponds to the capacity value of the second preset parameter;

T _r(n) the deviation coefficient of a second preset parameter with the sequence number n;

B _m a second business capability value of a store within the target base station area.

In an exemplary embodiment, determining the second business capability value of the stores in the target base station area is substantially an analytical evaluation of future construction development of the target base station area, wherein the analytical evaluation of data is performed on the ports, stations, and circled governments and large enterprises of the target base station area for the flow of people in the target base station area.

It should be noted that in the exemplary embodiment, other formulas may be used to analyze and evaluate the future construction development of the target base station area, and the above formula is only a reference.

In step S140, a site selection score of the target base station region is determined according to the second service capability value of the store in the target base station region, the position of the base station in the target base station region, and the positions of stores in the target base station region, and a construction optimization scheme of the store in the target base station region is determined according to the site selection score of the target base station region and a preset revenue value corresponding to the target base station region.

In an example embodiment, determining the address selection score value of the target base station area according to the second service capability value of the store in the target base station area, the position of the base station in the target base station area, and the positions of stores in the target base station area includes: extracting the position of a central base station in the target base station region from the positions of base stations in the target base station region, and extracting the position of a store nearest to the central base station from the positions of stores in the target base station region; calculating the distance between the position of the central base station and the position of the own store closest to the central base station; and determining the site selection score value of the target base station area according to the second service capability value and the distance of the store in the target base station area.

In an exemplary embodiment, the own store has a high cost, and the social store has a low cost, so that when the distance between the own store closest to the central base station and the central base station is less than a preset threshold, for example, 2 km, it is not considered whether or not the own store is built in the target base station area, and what type of social store is built.

In an exemplary embodiment, the address selection score value of the target base station area is determined according to the second service capability value and the distance of the stores in the target base station area, and the following formula may be referred to:

Q _m ＝B _m ×(1-2/Len)

Q _m : the site selection score value of the target base station area;

len: a distance (kilometers) between the position of the central base station and the position of the own store closest to the central base station in the target base station region;

It should be noted that when Q is used _m When the calculated result is less than 0, Q is taken _m 0. That is, when the distance between the position of the central base station and the position of the own store closest to the central base station in the target base station area is less than 2 km, Q is taken _m 0. The parameter 2 in this formula is only an example.

In an example embodiment, the type of the target base station area is an urban area type, the preset profit value corresponding to the target base station area is a preset profit value of each type of store corresponding to the urban area type, and a construction optimization scheme of the stores in the target base station area is determined according to the site selection score value of the target base station area and the preset profit value corresponding to the target base station area, and the construction optimization scheme includes: sequencing the preset income value of each type of store corresponding to the urban area type and the site selection score value of the target base station area according to the numerical value, determining the preset income value which is adjacent to the site selection score value and is smaller than the site selection score value in the sequencing, and determining the store type corresponding to the preset income value; and taking the determined store type as a first target type, and determining a construction optimization scheme of stores in the target base station area as a first target type added store in the target base station area.

In an exemplary embodiment, the stores are classified in advance by the basis of, including and not limited to, business area, location of central base station, customer, regional objects, and the like. An exemplary classification is as follows: dividing stores into self-owned stores and social stores, wherein the self-owned stores are divided into three types according to characteristics of business area, cost and the like, and the self-owned stores are below 80 square meters, 80-160 square meters and above 160 square meters; the social stores are divided into urban stores and rural stores according to characteristics of clients, regional objects and the like, wherein the urban stores are divided into stores, professional stores, cooperation halls and community stores, and the rural stores are divided into village and town halls and village-level stores. Then various types of stores corresponding to the urban area types include, but are not limited to: the self-owned store: below 80 square meters, 80-160 square meters, three types above 160 square meters and social stores: four types of stores, professional stores, cooperation halls and community stores. Different types of stores correspond to different types of preset profit values S _n . It should be noted that the urban area type may be subdivided into a core urban area type and a general urban area type, and the preset profit value of each type of store corresponding to the core urban area type is different from the preset profit value of each type of store corresponding to the general urban area type.

In an example embodiment, professional stores include, without limitation, corporate customer service integrators, end partners, broad channels, etc., for professional customer markets.

In an example embodiment, the preset profit value of each type of store may be determined according to parameters such as annual income, annual cost and the like, and is a fixed value calculated in advance. The reference formula for calculating the preset profit value of each type of store is as follows:

S _n ＝N _rn -N _cn -R _{n is fixed} /Y

S _n Presetting a revenue value in the year of a certain type of store;

N _rn : annual income for certain types of stores;

N _cn : annual cost of certain type of store, which is the business cost of the owned hall, including wages, rents, water and electricity, and the like; the social hall has the cost of remuneration, propaganda materials and the like;

R _{n is fixed} : the one-time fixed investment amount of the business hall is owned, and the social channel is 0;

y: the number of years of one-time fixed investment beach in the business hall of own is defined according to the financial requirement (the default value is 15 years).

In an example embodiment, the parameters of annual revenue, annual cost, etc. for each type of store are shown with reference to table 2.

TABLE 2

In an exemplary embodiment, when the target base station area is a core urban area type in the urban area types, the site selection score value Q of the target base station area is obtained _m Is mixing Q with _m The value of (a) is compared with the preset income value of each type store corresponding to the core urban area type. For example, in the own store in a core urban area: the type below 80 square meters corresponds to the preset profit value S ₁ The type of 80-160 square meters corresponds to a preset profit value S ₂ The type of more than 160 square meters corresponds to the preset income value S ₃ (ii) a In social stores in core urban areas: the preset profit value corresponding to the type of the store is S ₄ Professional shop correspondencePresetting the profit value as S ₅ The preset income value corresponding to the cooperation hall is S ₆ The corresponding preset income value of the community store is S ₇ . Will Q _m And S ₁ 、S ₂ 、S ₃ 、S ₄ 、S ₅ 、S ₆ And S ₇ And (6) sorting. If Q _m And S ₃ Adjacent and S ₃ <Q _m Then S will be ₃ And determining the corresponding store type, namely the own store type of the core urban area with the height of more than 160 square meters as a first target type, and further determining that the construction optimization scheme of the stores in the target base station area is the store with the own store type of the core urban area with the height of more than 160 square meters in the target base station area.

In an exemplary embodiment, when the target base station area is a general urban area type among the urban area types, the site selection score value Q of the target base station area is obtained _m Is mixing Q with _m The value of (a) is compared with the preset profit value of each type of store corresponding to the general urban area type. For example, in a typical urban area's own store: the type below 80 square meters corresponds to the preset profit value S ₁ The type of 80-160 square meters corresponds to a preset profit value S ₂ The type of more than 160 square meters corresponds to the preset income value S ₃ (ii) a In social stores in core urban areas: the preset profit value corresponding to the type of the store is S ₄ The corresponding preset income value of the professional store is S ₅ The preset income value corresponding to the cooperation hall is S ₆ The corresponding preset income value of the community store is S ₇ . Will Q _m And S ₁ 、S ₂ 、S ₃ 、S ₄ 、S ₅ 、S ₆ And S ₇ And (6) sorting. If Q _m And S ₅ Adjacent and S ₅ <Q _m Then S will be ₅ And determining the corresponding store type, namely the professional store type in the social stores in the general urban area as a first target type, and further determining that the construction optimization scheme of the stores in the target base station area is the store in which the professional store type in the social stores in the general urban area is added in the target base station area.

In an example embodiment, the type of the target base station region is a rural type, the preset profit value corresponding to the target base station region is a preset profit value of each type of store corresponding to the rural type, and a construction optimization scheme of stores in the target base station region is determined according to the site selection score value of the target base station region and the preset profit value corresponding to the target base station region, and the construction optimization scheme includes: sequencing the preset income values of various types of stores corresponding to the rural types and the site selection score value of the target base station area according to the numerical values, determining the preset income values which are adjacent to the site selection score value and smaller than the site selection score value in sequencing, and determining the store type corresponding to the preset income values; and taking the determined store type as a second target type, and determining the construction optimization scheme of stores in the target base station area as adding stores of the second target type in the target base station area.

In an exemplary embodiment, only social stores are considered in building optimization for a rural type base station area, not owned stores, due to the higher cost of owned stores. Thus, various types of stores corresponding to rural types include, and are not limited to: a social store: the village and town hall and the village-level store are two types.

In an exemplary embodiment, when the target base station area is a rural type in an urban type, an address score value Q of the target base station area is obtained _m Is mixing Q with _m The value of (a) is compared with the preset income value of each type of store corresponding to the rural type. For example, in a rural type social store: the preset income value corresponding to the type of the village and town hall is S ₁ The corresponding preset income value of the village-level store is S ₂ . Will Q _m And S ₁ 、S ₂ And (6) sorting. If Q _m And S ₂ Adjacent and S ₂ <Q _m Then S will be ₂ And determining the corresponding store type and the rural type social store village type as a second target type, and further determining that the construction optimization scheme of stores in the target base station area is to add rural type social store village type stores in the target base station area.

In an exemplary embodiment, in the optimization scheme for building stores in the target base station area, the number of the stores can be increased by modifying own houses into the stores, or by investing in the optimization scheme, an agent can establish a new social store.

It should be noted that in the embodiment, in the construction optimization scheme of stores in the target base station area, the number of the added stores may be 1, that is, only one store is added at a time, and the number may also be 3 or 4. In addition, after one store is added, the steps of determining the first service capability value, the service capability standard value, the second service capability value and the like of the stores in the target base station area are carried out again, and then whether the stores need to be added continuously is determined.

According to the construction optimization method for the stores in the base station area in the exemplary embodiment of fig. 1, first, a first service capability value of the stores in the target base station area is determined according to values of first service parameters of each base station area and the target base station area of the same type as the target base station area in a first geographical range in which the target base station area is located; determining a service capability standard value of an in-store in the target base station area according to first service capability values of in-store in each base station area and in-store in the target base station area which are in the same type as the target base station area in a first geographical range; if the first service capability value of the stores in the target base station area is smaller than the service capability standard value and the number of the stores in the target base station area is smaller than the preset number of the stores, determining a second service capability value of the stores in the target base station area according to values of second service parameters of each base station area and the target base station area which are in the same type as the target base station area in a second geographic range of the target base station area; and determining the site selection score value of the target base station area according to the second service capability value of the store in the target base station area, the position of the base station in the target base station area and the positions of all stores in the target base station area, and determining the construction optimization scheme of the stores in the target base station area according to the site selection score value of the target base station area and the preset income value corresponding to the target base station area. According to the embodiment of the invention, a first service capability value and a standard service capability value of the stores in the target base station area can be determined, whether the stores in the target base station area need to be optimized is determined according to a comparison result of the first service capability value and the standard service capability value, if the stores in the target base station area need to be optimized, a second service capability value is determined, a site selection score value of the target base station area is determined according to the second service capability value, the base station position and the store position, and a construction optimization scheme of the stores in the target base station area is determined according to a comparison result of the site selection score value and a preset profit value.

In an example embodiment, if the first service capacity value of the stores in the target base station area is smaller than the service capacity standard value of the stores in the target base station area, and the number of the stores in the target base station area is greater than the preset number of stores, the construction optimization scheme of the stores in the target base station area is determined as capacity promotion optimization for the stores in the target base station area. The capacity improvement optimization method is not limited to digging channels with strong competitive capacity, carrying out capacity assessment and carrying out final elimination. In this case, the number of stores in the target base station area is sufficient, and it is not necessary to add a new number of stores.

In an example embodiment, if the first service capability value of the stores in the target base station area is greater than the service capability standard value of the stores in the target base station area, and the number of the stores in the target base station area is less than the preset number of stores, the service capability of the stores in the target base station area exceeds the average level at this time, and building optimization of the stores in the target base station area is not needed, that is, the building optimization scheme of the stores in the target base station area is determined as no measure is taken.

In an example embodiment, if the first service capacity value of the stores in the target base station area is greater than the service capacity standard value of the stores in the target base station area, and the number of the stores in the target base station area is greater than the preset number of stores, the service capacity of the stores in the target base station area exceeds the average level at this time, and the stores in the target base station area do not need to be optimized for construction. Considering that the number of stores in the target base station area exceeds the preset number of stores, there may be a problem of high cost, and in this case, it may be evaluated through human intervention whether the number of stores in the target base station area needs to be reduced. Namely, the construction optimization scheme of the stores in the target base station area is determined as that no measures are taken or whether the number of the stores in the target base station area needs to be reduced or not is manually evaluated.

In an example embodiment, according to a first user operation, coordinate information in an electronic map is determined, and construction optimization information corresponding to a base station area corresponding to the coordinate information is displayed. The first user action includes, but is not limited to, a single click, a double click, and a long press. The construction optimization information corresponding to the base station area includes, but is not limited to, multiple index evaluation information such as development ability, customer value, pedestrian volume, geographic position, store area, store ability, and the like of stores in the base station area, and information related to a construction optimization scheme of the stores in the base station area. For example, when a user clicks a coordinate point of a large mall on an electronic map on an electronic device, the electronic device displays, beside the coordinate point, construction optimization information of a base station area where the large mall is located, such as the number of stores in the base station area, the amount of people in the base station area, a construction optimization scheme corresponding to the base station area, and a specific analysis process of the construction optimization scheme. It should be noted that if the content of the construction optimization information is too much, the coordinate information in the electronic map may be determined according to the first user operation, and the link including the construction optimization information corresponding to the base station area corresponding to the coordinate information may be displayed. After clicking the link, the user can jump to other interfaces to read detailed construction optimization information.

Fig. 2 is a schematic flow chart of a method for optimizing the construction of stores in a base station area according to another embodiment of the present disclosure.

Referring to fig. 2, in step S202, a preset profit value for each store type of the general province is defined.

In an exemplary embodiment, the stores are classified in advance by the basis of, including and not limited to, business area, location of central base station, customer, regional objects, and the like. An exemplary classification is as follows: dividing stores into self-owned stores and social stores, wherein the self-owned stores are divided into three types according to characteristics of business area, cost and the like, and the self-owned stores are below 80 square meters, 80-160 square meters and above 160 square meters; the social stores are divided into urban stores and rural stores according to characteristics of clients, regional objects and the like, wherein the urban stores are divided into stores, professional stores, cooperation halls and community stores, and the rural stores are divided into village and town halls and village-level stores. Then various types of stores corresponding to the urban area types include, but are not limited to: the self-owned store: the three types of the product are 80 square meters or less, 80-160 square meters and more than 160 square meters, and social stores: four types of stores, professional stores, cooperation halls and community stores. And different types of stores correspond to different types of preset profit values Sn. It should be noted that the urban area type may be subdivided into a core urban area type and a general urban area type, and the preset profit value of each type of store corresponding to the core urban area type is different from the preset profit value of each type of store corresponding to the general urban area type.

In step S204, the total province is divided into a plurality of base station regions.

In the exemplary embodiment, the province is originally divided into four levels of regions, namely province, state, county and grid from large to small. The invention further divides the grid area into a plurality of base station areas on the basis of four-level area division. Each base station area comprises one or more base station sectors, and the base station area is smaller than the grid area, and generally, the base station area in an urban area is a community or a cell; the base station area in the rural area is one or more villages or a village town. The base station area comprises at least one base station, generally, the center position of each base station area is a certain base station, and the floating population in the base station area exceeds 1000 people. The base station area may be a circular area, a square area, or an area with other preset shapes, which is not limited in the present invention. The different base station areas do not overlap each other. There may or may not be one or more stores within the base station area. Each store must be located within a certain base station area. The location of the base station area is determined based on the base station location.

In step S206, a first business capability value of stores in each base station area is determined.

In an example embodiment, a first service capability value of an store in the target base station area is determined according to values of a plurality of first preset parameters of the target base station area and values of a plurality of first preset parameters of base station areas of the same type as the target base station area in a first geographical range in which the target base station area is located.

In step S208, a standard business capability value is determined.

In an example embodiment, a median of first service capability values of stores in the province where the target base station region and the target base station region are located and the store in each base station region of the same type as the target base station region is obtained, and the median is determined as a standard service capability value of the target base station region.

In step S210, it is determined whether the store competitiveness is strong in the base station area.

In an example embodiment, a first business capability value of a store in the target base station area is compared with a business standard capability value, and if the first business capability value is greater than a business capability standard value, the store in the target base station area is strong in competitiveness; and if the first service capability value is smaller than the service capability standard value, the competitiveness of stores in the target base station area is not strong.

In step S212, it is determined whether the number of stores in the base station area is sufficient.

In an example embodiment, the number of stores within the target base station area is compared to a preset number of stores. The preset number of stores may be an average or median value of the number of stores in each base station region of the same type as the target base station region in the province in which the target base station region is located in the target base station region, or other user-defined values.

In step S214, a second business capability value of the store within the base station area is determined.

In an example embodiment, a second service capability value of an store in the target base station area is determined according to values of a plurality of second preset parameters of the target base station area and values of a plurality of second preset parameters of base station areas in a second geographical range where the target base station area is located, wherein the base station areas are of the same type as the target base station area.

In step S216, the site selection score value of the base station area is determined.

In an example embodiment, the location score value of the target base station area is determined according to a second service capability value of a store in the target base station area, a position of a center base station of the target base station area, and a position of a base station of an own store in the target base station area, which is closest to the position of the center base station.

In step S218, a construction optimization plan of the base station area is determined.

In an example embodiment, if the target base station area is an urban area type, the site selection score value of the target base station area and the preset revenue value of each store type corresponding to the urban area type are ranked, the store type corresponding to the preset revenue value which is adjacent to the site selection score value and smaller than the site selection score value is determined, and the construction optimization scheme of the target base station area is determined to be the store with the increased store type. The number of additional stores may be 1 or other numbers, but should not be too large.

In an example embodiment, if the target base station area is a rural type, the site selection score value of the target base station area and the preset revenue value of each store type corresponding to the rural type are ranked, a store type corresponding to the preset revenue value which is adjacent to the site selection score value and smaller than the site selection score value is determined, and the construction optimization scheme of the target base station area is determined to be a store which increases the store type. The number of additional stores may be 1 or other numbers, but should not be too large.

In step S220, store capacity is increased.

In an example embodiment, a method of store capacity boost includes, and is not limited to: and excavating a channel with strong competitive power, performing capability assessment, and performing final elimination.

In step S222, the next base station area is evaluated.

In an exemplary embodiment, after determining the construction optimization scheme of the target base station area or determining that the construction optimization of the target base station area is not needed, the next base station area is set as the target base station area, and the evaluation is restarted.

Fig. 3 is a schematic diagram of store classifications provided in one embodiment of the present description.

Referring to fig. 3, the stores are divided into a self store 302 and a social store 304. The self-owned stores 302 are divided into three types according to characteristics such as business area and cost, wherein the self-owned stores 306 are below 80 square meters, the self-owned stores 308 are 80-160 square meters, and the self-owned stores 310 are above 160 square meters; the social stores 304 are divided into urban stores 312 and rural stores 314 according to characteristics such as customers and regional objects, specifically, the urban stores 312 are further divided into stores 316, professional stores 318, collaboration hall 320, and community store 322, and the rural stores 314 are further divided into village halls 324 and village stores 326. It should be noted that this store classification is only one example.

Fig. 4 is a schematic diagram of an application scenario of base station area division according to an embodiment of the present disclosure.

Referring to fig. 4, each base station area in the map is a non-overlapping circular area, as shown by base station area 410, base station area 420, base station area 430, base station area 440, base station area 450, base station area 460, base station area 470, and base station area 480. The size of each base station area may be the same or different.

Referring to fig. 4 and table 3, the number of stores in each base station area may be different, and there may be no stores in the base station area.

TABLE 3

Base station area name	Number of stores
		Base station area 1	3
Base station area 2	0
		Base station area 3	11
Base station area 4	9
		Base station area 5	1
Base station area 6	6
		Base station area 7	3
Base station area 8	4

Fig. 5 is a schematic block diagram of a construction optimization apparatus for stores in a base station area according to an embodiment of the present invention.

Referring to fig. 5, the construction optimization apparatus 500 for stores in the base station area includes: a first service ability value determining module 510, a service ability standard value determining module 520, a second service ability value determining module 530 and a construction optimization scheme determining module 540.

The first service capability value determining module 510 is configured to determine a first service capability value of an store in a target base station region according to a value of a first service parameter of the target base station region and values of first service parameters of base station regions of the same type as the target base station region in a first geographic range in which the target base station region is located;

a service capability standard value determining module 520, configured to determine a service capability standard value of an store in the target base station area according to the first service capability value of the store in the target base station area and the first service capability value of the store in each base station area in the same type as the target base station area in the first geographic range;

a second service capability value determining module 530, configured to determine, if the first service capability value of the store in the target base station area is smaller than the service capability standard value of the store in the target base station area, and the number of the stores in the target base station area is smaller than the preset number of stores, a second service capability value of the store in the target base station area according to the value of the second service parameter of the target base station area, and the values of the second service parameters of base station areas of the same type as the target base station area in a second geographic range in which the target base station area is located;

and the construction optimization scheme determining module 540 is configured to determine the site selection score value of the target base station region according to the second service capability value of the store in the target base station region, the position of the base station in the target base station region, and the positions of stores in the target base station region, and determine the construction optimization scheme of the store in the target base station region according to the site selection score value of the target base station region and the preset profit value corresponding to the target base station region.

In some embodiments of the present invention, based on the foregoing scheme, the first service parameter includes a plurality of first preset parameters, and the first service capability value determining module 510 is specifically configured to:

for each first preset parameter, counting the value of the first preset parameter of the target base station area and the value of the first preset parameter of each base station area of the same type as the target base station area, and determining the maximum value, the minimum value and the median value corresponding to the first preset parameter;

determining the capacity value of the target base station area corresponding to the first preset parameter according to the value of the first preset parameter of the target base station area, the maximum value, the minimum value and the median value corresponding to the first preset parameter, the preset weight and the direction coefficient corresponding to the first preset parameter;

and summing the capability values of the target base station area corresponding to the first preset parameters to obtain a first service capability value of an store in the target base station area.

In some embodiments of the present invention, based on the foregoing solution, the service capability standard value determining module 520 is specifically configured to:

counting first service capability values of stores in the target base station area and first service capability values of stores in the base station areas of the same type as the target base station area in a first geographical range to obtain a median of the first service capability values;

and determining the median value of the first service capability value as a service capability standard value of the store in the target base station area.

In some embodiments of the present invention, based on the foregoing scheme, the second service parameter includes a plurality of second preset parameters, and the second service capability value determining module 530 is specifically configured to:

for each second preset parameter, counting the value of the second preset parameter of the target base station area and the value of the second preset parameter of each base station area of the same type as the target base station area, and determining the maximum value, the minimum value and the median value corresponding to the second preset parameter;

determining a capacity value of the target base station area corresponding to the second preset parameter according to the value of the second preset parameter of the target base station area, the maximum value, the minimum value and the median value corresponding to the second preset parameter, the preset weight and the direction coefficient corresponding to the second preset parameter;

and summing the capacity values of the target base station area corresponding to the second preset parameters to obtain a second service capacity value of the store in the target base station area.

In some embodiments of the present invention, based on the above scheme, the optimization scheme determining module 540 is specifically configured to:

extracting the position of a central base station in the target base station region from the positions of base stations in the target base station region, and extracting the position of a store nearest to the central base station from the positions of stores in the target base station region;

calculating the distance between the position of the central base station and the position of the own store closest to the central base station;

and determining the site selection score value of the target base station area according to the second service capability value and the distance of the store in the target base station area.

In some embodiments of the present invention, based on the above scheme, the type of the target base station area is an urban area type, the preset profit value corresponding to the target base station area is a preset profit value of each type of store corresponding to the urban area type, and the construction optimization scheme determining module 540 is specifically configured to:

sequencing the preset income value of each type of store corresponding to the urban area type and the site selection score value of the target base station area according to the numerical value, determining the preset income value which is adjacent to the site selection score value and is smaller than the site selection score value in the sequencing, and determining the store type corresponding to the preset income value;

and taking the determined store type as a first target type, and determining a construction optimization scheme of stores in the target base station area as a first target type added store in the target base station area.

In some embodiments of the present invention, based on the above scheme, the type of the target base station area is a rural type, the preset profit value corresponding to the target base station area is a preset profit value of each type of store corresponding to the rural type, and the construction optimization scheme determining module 540 is specifically configured to:

sequencing the preset income values of various types of stores corresponding to the rural types and the site selection score value of the target base station area according to the numerical values, determining the preset income values which are adjacent to the site selection score value and smaller than the site selection score value in sequencing, and determining the store type corresponding to the preset income values;

and taking the determined store type as a second target type, and determining the construction optimization scheme of stores in the target base station area as adding stores of the second target type in the target base station area.

According to the technical scheme of the embodiment of the invention, firstly, a first service capability value of an store in a target base station area is determined according to values of first service parameters of each base station area and the target base station area of the same type as the target base station area in a first geographical range in which the target base station area is located; determining a service capability standard value of an in-store in the target base station area according to first service capability values of in-store in each base station area and in-store in the target base station area which are in the same type as the target base station area in a first geographical range; if the first service capability value of the stores in the target base station area is smaller than the service capability standard value and the number of the stores in the target base station area is smaller than the preset number of the stores, determining a second service capability value of the stores in the target base station area according to values of second service parameters of each base station area and the target base station area which are in the same type as the target base station area in a second geographic range of the target base station area; and determining the site selection score value of the target base station area according to the second service capability value of the store in the target base station area, the position of the base station in the target base station area and the positions of all stores in the target base station area, and determining a construction optimization scheme of the store in the target base station area according to the site selection score value of the target base station area and a preset income value corresponding to the target base station area. According to the embodiment of the invention, the first service capability value and the standard service capability value of the stores in the target base station area can be determined, whether the stores in the target base station area need to be optimized is determined according to the comparison result of the first service capability value and the standard service capability value, if the stores in the target base station area need to be optimized, the second service capability value is determined, the site selection score value of the target base station area is determined according to the second service capability value, the base station position and the store position, and the construction optimization scheme of the stores in the target base station area is determined according to the comparison result of the site selection score value and the preset profit value.

It should be noted that the construction optimization device for stores in a base station area provided in the embodiment of the present invention can implement the processes of the construction optimization method for stores in a base station area, and achieve the same functions and effects, which are not repeated here.

Further, an embodiment of the present specification further provides a construction optimization device for stores in a base station area, and fig. 6 is a schematic structural diagram of the construction optimization device for stores in the base station area provided in the embodiment of the present specification, as shown in fig. 6, the device includes: memory 601, processor 602, bus 603, and communication interface 604. The memory 601, processor 602, and communication interface 604 communicate via bus 603. the communication interface 604 may include input and output interfaces including, but not limited to, a keyboard, mouse, display, microphone, and the like.

In fig. 6, the memory 601 stores thereon computer-executable instructions executable on the processor 602, and when executed by the processor 602, the computer-executable instructions implement the following processes:

determining a service capability standard value of the store in the target base station area according to the first service capability value of the store in the target base station area and the first service capability value of the store in each base station area of the same type as the target base station area in the first geographical range;

Optionally, when the computer executable instructions are executed by the processor, the first service parameter includes a plurality of first preset parameters, and the determining, according to the value of the first service parameter of the target base station region and the values of the first service parameter of each base station region of the same type as the target base station region within the first geographic range in which the target base station region is located, a first service capability value of an store within the target base station region includes:

Optionally, when executed by the processor, the computer executable instructions determine the standard value of the service capability of the stores in the target base station area according to the first service capability value of the stores in the target base station area and the first service capability value of the stores in each base station area of the same type as the target base station area in the first geographical range, including:

counting a first service capability value of an store in the target base station area and first service capability values of stores in base station areas of the same type as the target base station area in a first geographical range to obtain a median of the first service capability values;

Optionally, when the computer executable instructions are executed by the processor, the second service parameter includes a plurality of second preset parameters, and the determining, according to the value of the second service parameter of the target base station region and the values of the second service parameter of each base station region in the second geographic range where the target base station region is located, which is of the same type as the target base station region, the second service capability value of the store in the target base station region includes:

for each second preset parameter, counting the value of the second preset parameter of the target base station area and the value of the second preset parameter of each base station area of the same type as the target base station area, and determining the maximum value, the minimum value and the median corresponding to the second preset parameter;

Optionally, when executed by the processor, the computer executable instructions determine an address selection score value of the target base station area according to the second service capability value of the store in the target base station area, the position of the base station in the target base station area, and the positions of stores in the target base station area, and include:

Optionally, when the computer executable instruction is executed by the processor, the type of the target base station area is an urban area type, the preset profit value corresponding to the target base station area is a preset profit value of each type of store corresponding to the urban area type, and a construction optimization scheme of the stores in the target base station area is determined according to the site selection score value of the target base station area and the preset profit value corresponding to the target base station area, where the construction optimization scheme includes:

and taking the determined store type as a first target type, and determining the construction optimization scheme of stores in the target base station area as adding stores of the first target type in the target base station area.

Optionally, when the computer executable instruction is executed by the processor, the type of the target base station region is a rural type, the preset profit value corresponding to the target base station region is a preset profit value of each type of store corresponding to the rural type, and a construction optimization scheme of the stores in the target base station region is determined according to the site selection score value of the target base station region and the preset profit value corresponding to the target base station region, where the construction optimization scheme includes:

According to the technical scheme of the embodiment of the invention, firstly, a first service capability value of an store in a target base station area is determined according to values of first service parameters of each base station area and the target base station area of the same type as the target base station area in a first geographical range in which the target base station area is located; determining a service capability standard value of an in-store in the target base station area according to first service capability values of in-store in each base station area and in-store in the target base station area which are in the same type as the target base station area in a first geographical range; if the first service capability value of the stores in the target base station area is smaller than the service capability standard value and the number of the stores in the target base station area is smaller than the preset number of the stores, determining a second service capability value of the stores in the target base station area according to values of second service parameters of each base station area and the target base station area which are in the same type as the target base station area and are in a second geographical range of the target base station area; and determining the site selection score value of the target base station area according to the second service capability value of the store in the target base station area, the position of the base station in the target base station area and the positions of all stores in the target base station area, and determining the construction optimization scheme of the stores in the target base station area according to the site selection score value of the target base station area and the preset income value corresponding to the target base station area. According to the embodiment of the invention, a first service capability value and a standard service capability value of the stores in the target base station area can be determined, whether the stores in the target base station area need to be optimized is determined according to a comparison result of the first service capability value and the standard service capability value, if the stores in the target base station area need to be optimized, a second service capability value is determined, a site selection score value of the target base station area is determined according to the second service capability value, the base station position and the store position, and a construction optimization scheme of the stores in the target base station area is determined according to a comparison result of the site selection score value and a preset profit value.

The construction optimization device for stores in a base station area provided in an embodiment of this specification can implement the processes in the aforementioned method for optimizing the construction of stores in a base station area, and achieve the same functions and effects, which are not repeated here.

Further, another embodiment of the present specification also provides a storage medium for storing computer-executable instructions, which when executed by a processor implement the following process:

determining a first service capability value of a store in the target base station region according to the value of the first service parameter of the target base station region and the value of the first service parameter of each base station region of the same type as the target base station region in the first geographical range in which the target base station region is located;

for each first preset parameter, counting the value of the first preset parameter of the target base station area and the value of the first preset parameter of each base station area of the same type as the target base station area, and determining the maximum value, the minimum value and the median corresponding to the first preset parameter;

and summing the capability values of the target base station area corresponding to the first preset parameters to obtain a first service capability value of a store in the target base station area.

and determining the median value of the first service capability value as a standard service capability value of a store in the target base station area.

Optionally, when the computer executable instruction is executed by the processor, the type of the target base station region is an urban region type, the preset profit value corresponding to the target base station region is a preset profit value of each type of store corresponding to the urban region type, and a construction optimization scheme of the stores in the target base station region is determined according to the site selection score value of the target base station region and the preset profit value corresponding to the target base station region, where the construction optimization scheme includes:

sequencing the preset profit values of the stores of various types corresponding to the rural types and the site selection score value of the target base station area according to the numerical values, determining the preset profit values which are adjacent to the site selection score value and smaller than the site selection score value in sequencing, and determining the store type corresponding to the preset profit values;

According to the technical scheme of the embodiment of the invention, firstly, a first service capability value of a store in a target base station area is determined according to values of first service parameters of each base station area and the target base station area which are in the same type as the target base station area in a first geographical range in which the target base station area is located; determining a service capability standard value of an in-store in the target base station area according to first service capability values of in-store in each base station area and in-store in the target base station area which are in the same type as the target base station area in a first geographical range; if the first service capability value of the stores in the target base station area is smaller than the service capability standard value and the number of the stores in the target base station area is smaller than the preset number of the stores, determining a second service capability value of the stores in the target base station area according to values of second service parameters of each base station area and the target base station area which are in the same type as the target base station area in a second geographic range of the target base station area; and determining the site selection score value of the target base station area according to the second service capability value of the store in the target base station area, the position of the base station in the target base station area and the positions of all stores in the target base station area, and determining the construction optimization scheme of the stores in the target base station area according to the site selection score value of the target base station area and the preset income value corresponding to the target base station area. According to the embodiment of the invention, the first service capability value and the standard service capability value of the stores in the target base station area can be determined, whether the stores in the target base station area need to be optimized is determined according to the comparison result of the first service capability value and the standard service capability value, if the stores in the target base station area need to be optimized, the second service capability value is determined, the site selection score value of the target base station area is determined according to the second service capability value, the base station position and the store position, and the construction optimization scheme of the stores in the target base station area is determined according to the comparison result of the site selection score value and the preset profit value.

The storage medium includes a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.

The storage medium provided in an embodiment of the present specification can implement the processes in the aforementioned method for optimizing construction of stores in a base station area, and achieve the same functions and effects, which are not repeated here.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include transitory computer readable media (transmyedia) such as modulated data signals and carrier waves.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A construction optimization method for stores in a base station area is characterized by comprising the following steps:

in the multiple first preset parameters, for each first preset parameter, counting the value of the first preset parameter of a target base station region and the value of the first preset parameter of each base station region of the same type as the target base station region in a first geographical range where the target base station region is located, and determining the maximum value, the minimum value and the median value corresponding to the first preset parameter;

determining the capacity value of the target base station area corresponding to the first preset parameter according to the value of the first preset parameter of the target base station area, the maximum value, the minimum value and the median corresponding to the first preset parameter, and the preset weight and the direction coefficient corresponding to the first preset parameter;

summing the capacity values of the target base station area corresponding to the first preset parameters to obtain a first service capacity value of an store in the target base station area;

if the first service capability value of the stores in the target base station area is smaller than the service capability standard value of the stores in the target base station area, and the number of the stores in the target base station area is smaller than the preset number of stores, determining a second service capability value of the stores in the target base station area according to the value of a second service parameter of the target base station area and the values of second service parameters of base station areas of the same type as the target base station area in a second geographic range where the target base station area is located; the second geographic range is less than the first geographic range;

extracting the position of a central base station in the target base station region from the positions of base stations in the target base station region, and extracting the position of a self store nearest to the central base station from the positions of stores in the target base station region;

calculating the distance between the position of the central base station and the position of the nearest own store to the central base station;

determining a site selection score value of the target base station area according to a second service capability value of an store in the target base station area and the distance;

and determining a construction optimization scheme of an store in the target base station region according to the site selection score value of the target base station region and a preset income value corresponding to the target base station region.

2. The method of claim 1, wherein determining the standard value of the service capability of the store in the target base station area based on the first service capability value of the store in the target base station area and the first service capability value of the stores in each base station area of the same type as the target base station area in the first geographic area comprises:

counting a first service capability value of an store in the target base station region and first service capability values of stores in base station regions of the same type as the target base station region in the first geographical range to obtain a median of the first service capability values;

and determining the median value of the first service capability value as a service capability standard value of a store in the target base station area.

3. The method of claim 1, wherein the second traffic parameter comprises a plurality of second preset parameters, and wherein determining the second traffic capability value of the store in the target base station region according to the value of the second traffic parameter of the target base station region and the values of the second traffic parameter of each base station region of the same type as the target base station region in the second geographical range in which the target base station region is located comprises:

for each second preset parameter, counting the value of the second preset parameter of the target base station region and the value of the second preset parameter of each base station region of the same type as the target base station region, and determining the maximum value, the minimum value and the median corresponding to the second preset parameter;

and summing the capacity values of the target base station area corresponding to the second preset parameters to obtain a second service capacity value of an store in the target base station area.

4. The method according to claim 1, wherein the type of the target base station area is an urban area type, the preset profit value corresponding to the target base station area is a preset profit value of each type of store corresponding to the urban area type, and the determining of the construction optimization scheme of the stores in the target base station area according to the site selection score value of the target base station area and the preset profit value corresponding to the target base station area comprises:

sequencing the preset income values of various types of stores corresponding to the urban area types and the site selection score value of the target base station area according to the numerical values, determining the preset income value which is adjacent to the site selection score value and is smaller than the site selection score value in sequencing, and determining the store type corresponding to the preset income value;

and taking the determined store type as a first target type, and determining a construction optimization scheme of stores in the target base station area as adding stores of the first target type in the target base station area.

5. The method according to claim 1, wherein the type of the target base station area is a rural type, the preset profit value corresponding to the target base station area is a preset profit value of each type of store corresponding to the rural type, and the determining of the construction optimization scheme of the stores in the target base station area according to the address score value of the target base station area and the preset profit value corresponding to the target base station area comprises:

and taking the determined store type as a second target type, and determining a construction optimization scheme of stores in the target base station area as adding stores of the second target type in the target base station area.

6. A construction optimization device for shops in a base station area is characterized by comprising:

a first service capability value determining module, configured to count, for each first preset parameter in a plurality of first preset parameters, a value of the first preset parameter of a target base station region and values of the first preset parameter of base station regions of the same type as the target base station region within a first geographic range where the target base station region is located, and determine a maximum value, a minimum value, and a median value corresponding to the first preset parameter; determining the capacity value of the target base station area corresponding to the first preset parameter according to the value of the first preset parameter of the target base station area, the maximum value, the minimum value and the median value corresponding to the first preset parameter, and the preset weight and the direction coefficient corresponding to the first preset parameter; summing the capacity values of the target base station area corresponding to the first preset parameters to obtain a first service capacity value of a store in the target base station area;

the service capability standard value determining module is used for determining a service capability standard value of an store in the target base station area according to a first service capability value of the store in the target base station area and a first service capability value of the store in each base station area in the same type as the target base station area in the first geographical range;

a second service capability value determining module, configured to determine, if a first service capability value of an store in the target base station area is smaller than a service capability standard value of the store in the target base station area, and the number of the stores in the target base station area is smaller than a preset number of stores, a second service capability value of the store in the target base station area according to a value of a second service parameter of the target base station area and values of second service parameters of base station areas of the same type as the target base station area in a second geographical range in which the target base station area is located; the second geographic range is less than the first geographic range;

the construction optimization scheme determining module is used for extracting the position of a central base station in the target base station region from the positions of base stations in the target base station region and extracting the position of a self store nearest to the central base station from the positions of stores in the target base station region; calculating the distance between the position of the central base station and the position of the nearest own store to the central base station; determining a site selection score value of the target base station area according to a second service capability value of a store in the target base station area and the distance; and determining a construction optimization scheme of an store in the target base station region according to the site selection score value of the target base station region and a preset income value corresponding to the target base station region.

7. An apparatus for optimizing the construction of stores in a base station area, comprising a memory and a processor, the memory having stored thereon computer-executable instructions that, when executed on the processor, are capable of implementing the method for optimizing the construction of stores in a base station area as claimed in any one of claims 1 to 5.

8. A storage medium having computer-executable instructions stored therein, wherein the computer-executable instructions, when executed by a processor, are capable of implementing a method for optimizing the construction of stores within a base station area as claimed in any one of claims 1 to 5.