CN112288550B

CN112288550B - Regional order analysis method, system and computer readable medium

Info

Publication number: CN112288550B
Application number: CN202011301684.0A
Authority: CN
Inventors: 王泰舟
Original assignee: Shiheng Shanghai Technology Service Co ltd
Current assignee: Shiheng Shanghai Technology Service Co ltd
Priority date: 2020-11-19
Filing date: 2020-11-19
Publication date: 2022-11-22
Anticipated expiration: 2040-11-19
Also published as: CN112288550A

Abstract

The invention provides a regional order analysis method, a regional order analysis system and a computer readable medium. The regional order analysis method comprises the following steps: acquiring a plurality of orders; acquiring city grid information according to city map data, wherein the city grid information comprises a plurality of city grids; establishing a city order distribution model, and generating longitude and latitude information of each order in the plurality of orders by using the city order distribution model; judging the city grid in which each order falls according to the longitude and latitude information of each order; associating a city grid with one or more orders falling within the city grid; and calculating order data of an area formed by the plurality of city grids.

Description

Regional order analysis method, system and computer readable medium

Technical Field

The present invention relates to the field of internet technologies, and in particular, to a method and a system for analyzing a regional order, and a computer-readable medium.

Background

With the rapid development of technologies such as the internet and big data, various technologies related to the internet and big data have been deeply applied to aspects of social life. Many stores receive orders from internet platforms and provide services such as food and drink, take-out, delivery, etc. In some scenarios, data of a certain area (e.g., business district) needs to be deeply analyzed in order to operate more finely. However, no suitable tool is currently available to analyze and display the order data for the region.

Disclosure of Invention

The technical problem to be solved by the invention is to provide a regional order analysis method, system and computer readable medium, which can perform position or coordinate-based analysis on orders in one or more regions.

In order to solve the technical problem, the invention provides a regional order analysis method, which comprises the following steps: acquiring a plurality of orders; acquiring city grid information according to city map data, wherein the city grid information comprises a plurality of city grids; establishing a city order distribution model, and generating longitude and latitude information of each order in the multiple orders by using the city order distribution model; judging the city grid in which each order falls according to the longitude and latitude information of each order; associating a city grid with one or more orders falling within the city grid; and calculating order data of an area formed by the plurality of city grids.

In an embodiment of the present invention, the step of obtaining city grid information according to city map data includes: drawing a grid at a plurality of coordinate points in the city map data; and converting the plane coordinate system of the urban map data into a curved surface coordinate system, and converting the longitude and latitude information in the urban map data into real coordinate information.

In an embodiment of the present invention, the step of establishing the city order distribution model includes: establishing a real city order distribution model as a target model by using actual data; giving a rough order distribution range; and calculating a rough model of the urban order distribution model in the order distribution range by using a fitting algorithm, comparing the rough model with the target model, adjusting parameters of the rough model according to a comparison result until the rough model is consistent with the target model, and outputting an optimal urban order distribution model.

In an embodiment of the present invention, the step of generating longitude and latitude information of each of the plurality of orders comprises: drawing a concentric circle by taking the coordinate of the store as a central point and the boundary value of the distribution distance as a radius; and randomly generating coordinate points in the covered area of the concentric circles and giving orders.

In an embodiment of the present invention, the step of determining the city grid into which each order falls according to the longitude and latitude information of each order includes: converting the latitude and longitude information into a geohash value through a geohash algorithm; generating a grid set saved in the urban grid process through the geohash value query; and judging the grid in which the latitude and longitude information is positioned by a ray method.

In an embodiment of the present invention, the city grid includes an effective city grid and an ineffective city grid, and when the city grid in which each order falls is determined according to the longitude and latitude information of each order, the method further includes: when the longitude and latitude information of the order falls into the invalid city grid, redistributing the city grid into which the order falls; and when the longitude and latitude information of the order falls into the effective city grid, establishing the association between the order and the effective city grid.

In one embodiment of the present invention, the step of reassigning the city grid into which the order falls comprises: selecting city grids of a plurality of circles around the invalid city grid, and sequentially reducing the priorities from the inner circle to the outer circle; and if the first circle contains the effective city grids, the order is averagely distributed to the effective city grids, if the first circle does not contain the effective city grids, the second circle is taken, and the like, and if the last circle still contains no effective city grids, the order is lost.

In an embodiment of the present invention, the step of obtaining the city grid information according to the city map data includes marking the invalid city grid with an invalid area color card in the city map data.

Another aspect of the invention provides a regional order analysis system comprising a memory for storing instructions executable by a processor; and a processor for executing the instructions to implement the method as described above.

Another aspect of the invention proposes a computer readable medium having stored computer program code which, when executed by a processor, implements the method as described above.

Compared with the prior art, the method generates the longitude and latitude information of the order according to the urban order distribution model, and then judges the urban grid in which the order falls according to the longitude and latitude information of the order. This way, the order distribution is balanced and consistent with common knowledge, and the order characteristics of the area can be correctly reflected.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the principle of the invention. In the drawings:

fig. 1 is a block diagram of an area order analysis system according to an embodiment of the present application.

Fig. 2 is a flowchart of a method for analyzing a regional order according to an embodiment of the present application.

Fig. 3 is a flowchart of city map calculation according to an embodiment of the present application.

Fig. 4 is a schematic grid diagram in a city map according to an embodiment of the present application.

FIG. 5 is a schematic view of a region according to an embodiment of the present application.

FIG. 6 is a single grid schematic of an embodiment of the present application.

Fig. 7 is a schematic diagram of coordinate system conversion according to an embodiment of the present application.

Fig. 8 is a diagram illustrating a result of analyzing a regional order according to an embodiment of the present application.

Fig. 9 is a hardware implementation environment of a regional order analysis system according to an embodiment of the present application.

Detailed Description

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings used in the description of the embodiments will be briefly introduced below. It is obvious that the drawings in the following description are only examples or embodiments of the application, from which the application can also be applied to other similar scenarios without inventive effort for a person skilled in the art. Unless otherwise apparent from the context, or stated otherwise, like reference numbers in the figures refer to the same structure or operation.

As used in this application and the appended claims, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are intended to be inclusive in the plural unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.

The relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present application unless specifically stated otherwise. Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description. Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate. In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.

It should be noted that the terms "first", "second", and the like are used to define the components, and are only used for convenience of distinguishing the corresponding components, and the terms have no special meanings unless otherwise stated, and therefore, the scope of protection of the present application is not to be construed as being limited. Further, although the terms used in the present application are selected from publicly known and used terms, some of the terms mentioned in the specification of the present application may be selected by the applicant at his or her discretion, the detailed meanings of which are described in relevant parts of the description herein. Further, it is required that the present application is understood, not simply by the actual terms used but by the meaning of each term lying within.

It will be understood that when an element is referred to as being "on," "connected to," "coupled to" or "contacting" another element, it can be directly on, connected or coupled to or contacting the other element or intervening elements may be present. In contrast, when an element is referred to as being "directly on," "directly connected to," "directly coupled to" or "directly contacting" another element, there are no intervening elements present. Similarly, when a first component is said to be "in electrical contact with" or "electrically coupled to" a second component, there is an electrical path between the first component and the second component that allows current to flow. The electrical path may include capacitors, coupled inductors, and/or other components that allow current to flow even without direct contact between the conductive components.

The embodiments of the present application describe a regional order analysis method and system that can analyze orders in a certain region and integrate and present them according to coordinates (or locations).

In the context of the present application, an area is a geographical area in a city, such as an administrative or business area (or business circle). The order is an item purchased from a store, such as take-out, clothing. Or the order is a service purchased from a store, such as a movie, a restaurant, education, etc. The coordinates may be geographic coordinates associated with the store. In one example, the geographic coordinates are latitude and longitude.

An area may be divided into multiple grids so that orders in the area are matched to the grids. For example, the grid where the specified address is located and several (e.g., tens) of grids around the specified address constitute one area. In one embodiment, a city map is processed to obtain a city map comprising a grid.

Fig. 1 is a block diagram of an area order analysis system according to an embodiment of the present application. Referring to FIG. 1, the system 100 includes a number bin 101, an order consolidation module 102, a map calculation module 103, and an area calculation module 104. The bins 101 are adapted to collect store data for use, such as orders. The order collating module 102 is configured to obtain data such as orders from the bins 101, collate the data, and provide the collated data to the area calculating module 104. On the other hand, the map processing module 103 is configured to obtain city grid information according to the city map data, and provide the city grid information to the area calculation module 104. The region calculation module 104 performs a series of calculations by combining the order and the city grid information, and finally calculates order data in the region.

Fig. 2 is a flowchart of a method for analyzing a regional order according to an embodiment of the present application. Referring to fig. 2, the method for analyzing a regional order of the present embodiment includes the following steps:

at step 201, a plurality of orders are obtained.

Here, the order may be the original store order provided by the data warehouse 101. The order does not contain coordinate information such as latitude and longitude data. The order consolidation module 102 obtains the original order data through the connection data warehouse 101.

In step 202, city grid information is obtained from the city map data. The city grid information includes a plurality of city grids.

For example, the map processing module 103 may be invoked to obtain city grid information. Fig. 4 is a schematic diagram of a city grid according to an embodiment of the present application. FIG. 5 is a schematic view of a region according to an embodiment of the present application. Referring to fig. 4, most or all of the area of a city may cover the city grid. Referring to fig. 5, the city grid is any one of all hexagonal grids in one city. Many urban grids constitute the roughly large hexagonal grid shown in fig. 5.

In one embodiment, a valid city grid and an invalid city grid are distinguished. An active city grid is a grid in a collection of city grids, residential, office, commercial, and road, etc. An invalid city grid is a grid in a park, river, lake, mountain, etc. in a set of city grids.

At step 203, a city order distribution model is established and longitude and latitude information for each of the plurality of orders is generated using the city order distribution model.

The city order distribution model defines how orders are distributed in various geographic locations in a city. The order data typically contains only information about the store that placed the order, and no geographical location from which the order originated. Therefore, in an embodiment of the application, a city order distribution model is established, and the city order distribution model is called to generate the geographic position of each order, which is defined by longitude and latitude information.

In one embodiment, the order distribution model is a mathematical model that is fitted by the order box 101 through a fitting algorithm to best fit the order distribution rule. More specifically, a real city order distribution model is established as a target model using actual data. For example, the orders in one area of a city are investigated, and the geographical position distribution of each order is known, so that a real city order distribution model is established. Then, a rough order distribution range is given, such as 0-100 meters, 100-500 meters, or 500-1000 meters. This range is the range from which orders from a certain store originate. This range may be determined empirically and may be adjusted in subsequent processes. A rough model of the city order distribution model is then calculated using a fitting algorithm. In this process, a distribution rule within the distribution of orders may be used for fitting. For example, with a store as a center, orders generated by the store are distributed into a plurality of areas within the order distribution range according to a certain proportion, and then each order is randomly scattered into the areas. And comparing the obtained rough model with the target model, adjusting the parameters of the rough model according to the comparison result until the rough model is consistent with the target model, and outputting an optimal city order distribution model.

In one embodiment, the order arrangement module 102 generates longitude and latitude information for the order according to the order distribution model of the above step, and the longitude and latitude production algorithm of the order is generated for the random coordinates. For example, a concentric circle is drawn with the coordinates of a store as the center point and the boundary value of the distribution distance as the radius, and coordinate points are randomly generated in the area covered by the concentric circle and given to an order.

When the range order proportion model and the coordinate random production algorithm are not used, orders are unevenly distributed in the thermal order distribution diagram, a large number of orders appear in places (such as an unoccupied water area) where orders are absent, the thermal order distribution diagram is not real, and information of real areas cannot be reflected. After the proportional model is used, the order distribution is balanced and accords with the common sense, and the due order characteristics of the area can be correctly reflected.

In step 204, the city grid where each order falls is judged according to the latitude and longitude information of each order.

In one embodiment, the specific method is as follows: converting longitude and latitude information of the order into a geohash value through a geohash algorithm; generating a grid set saved in a city grid generation process by inquiring the geohash value; and judging the grid in which the longitude and latitude information is positioned by a ray method.

When the city grid distinguishes between valid and invalid grids, a further determination may be made as to whether a valid or invalid grid falls within. When the longitude and latitude information of the order falls into the invalid city grid, redistributing the city grid into which the order falls; and when the longitude and latitude information of the order falls into the effective city grid, establishing the association between the order and the effective city grid. Referring to FIG. 5, in one embodiment, the step of reallocating the city grid into which the order falls includes: selecting city grids of a plurality of circles (red circles in the figure, for example, 4) around the invalid city grid, and sequentially reducing the priorities from the inner circle to the outer circle; and if the first circle contains the effective city grids, the order is averagely distributed to the effective city grids, if the first circle does not contain the effective city grids, the second circle is taken, and the like, and if the last circle still contains no effective city grids, the order is discarded.

At step 205, the city grid is associated with one or more orders that fall within the city grid.

Here, the city grid information and the order data in the grid are stored after being associated with each other, and are submitted to the area calculation module 104.

At step 206, order data for an area comprised of a plurality of city grids is calculated.

Here, the area calculation module 104 centers on each individual grid and 60 grids around the grid constitute an area, and calculates order data in the area. Fig. 8 is a diagram illustrating a result of analyzing a regional order according to an embodiment of the present application. Referring to fig. 8, after a user inputs an address, order data in an area composed of 60 grids around the address may be calculated centering on the grid where the address is located. For example, 723 merchant counts in the area, and the takeout month order is 99.2w order, so that the user can accurately know the business information in the area. In addition, the order can be displayed according to item data, so that a user can know information of a certain interested item.

In addition, the step can also inform related personnel that the calculation is finished, and trigger a data backup mechanism to backup the historical area data. The historical data is backed up for error backtracking and to optimize the city order distribution model.

Fig. 3 is a flowchart of city map calculation according to an embodiment of the present application. Referring to fig. 3, the city map calculation process of the present embodiment is as follows.

At step 301, city map data and invalid area color chips are obtained.

In this step, the user may submit the city name of the city grid and the color code of the invalid area of the map, and the valid or invalid area can be seen through the color code. Since the background color of the same type of region is always the same, we can mark a series of invalid regions with the background color. For example, blue waters and green vegetation are inactive areas. The map processing module 103 of the system 100 may obtain the city map data and the invalid area color card for subsequent processing.

At step 302, a grid is drawn at a plurality of coordinate points in the city map data.

For example, gao Deyun is called to obtain the maximum longitude and latitude and the minimum longitude and latitude of the city geographic coordinates, and the maximum longitude and latitude and the minimum longitude and latitude are used as reference coordinates to draw the city grid.

In one example, the grid is drawn as a regular hexagon with a radius of 500 meters, as shown in FIG. 6. The city longitude and latitude range is the longitude and latitude range from the northwest corner to the southeast corner of a city on the map. The grid drawing sequence can be that firstly, the grid is drawn transversely from west to east, and then, a row of grid is drawn transversely again after the grid meets the condition. An exemplary sequence is to draw a first grid starting with the coordinate point of the northwest corner as point 1 of the first grid; the second grid draws the second grid with point 3 of the first grid as its point 1; the third grid is drawn with point 5 of the second grid as its point 1; the subsequent grid is drawn horizontally, and so on, namely: an odd number N of grids, with point 5 of the previous grid (N-1) plotted as its point 1; the even M-th grid, point 3 of the previous grid (M-1) is plotted as its point 1. Until the point 4 of a certain grid is larger than the longitude of the city range, the horizontal drawing of the row is finished, and the horizontal drawing of the next row is started. When the drawing is started on the X-th line, the drawing is started with the point 6 of the first grid in one or more lines of the first grid of the line as the point 2, and the horizontal drawing rule is the same as the above rule. And when the point 5 of the first grid of a certain row is smaller than the latitude of the city range, drawing the last row of the city, and finishing the drawing after the transverse drawing is finished. And recording the coordinates of 6 points of each grid and the geohash value of the coordinate points in the drawing calculation, and numbering the grids.

In step 303, the plane coordinate system is converted into a curved surface coordinate system, and the longitude and latitude information on the plane is converted into real and effective coordinate information.

Specifically, in the above-described hexagonal drawing process, if the idea of the process implemented is in a plane coordinate system, distortion of the figure deformation occurs. This is because the earth is a spherical surface, and the sensory distance of a straight line of 500 m on the plane surface is greater than that on the curved surface.

Here, the plane length calculation rule algorithm is converted into a spherical geometric length calculation method. As shown in fig. 7, when the angle AOB (center angle) is θ, the radius of the earth is R, the latitude and longitude of the point a are (x 1, y 1), and the latitude and longitude of the point B are (x 2, y 2), the spherical distance between the two points A, B is R θ.

The spherical distance calculation formula is as follows:

d(x1,y1,x2,y2)＝R*arccos(sin(x1)*sin(x2)+cos(x1)*cos(x2)*cos(y1-y2))

where x1, y1 are units of radians of latitude/longitude.

And when y1= y2, the formula becomes: d = R x | x1-x2 non-conducting phosphor

The plane regular hexagon can distort and deform on the earth curved surface, and after the plane hexagon conversion algorithm of the embodiment is adopted, the plane hexagon coordinates are converted into the spherical coordinates, the hexagon is displayed on a map and does not distort and deform any more.

At step 304, city map grid coordinate data is generated.

In this step, each grid coordinate data may be generated using the city grid of step 302 and the coordinate conversion result of step 303.

In step 305, a picture including a city grid graph is generated according to the generated grid coordinate data.

In step 306, the generated picture and the invalid color card are calculated together, and the invalid grid and the invalid order proportion are marked.

In one embodiment, a graphical computing unit is used to perform this computation. The graph calculation unit identifies and calculates invalid grids, and calculates the area of each grid. The calculated result data contains the number of the invalid grid, the proportion of the invalid orders in the invalid grid and the area information of each grid.

Because an invalid color card is submitted, if the grid is completely filled with the invalid color, the grid is 100% invalid, i.e., all orders falling in the grid are invalid orders, and all recalculations are made. If the invalid color only occupies a part of the grid, the graphic computing unit calculates the proportion of the part of the invalid color in the grid, and the proportion is the proportion of the invalid order in the grid.

For example, in a grid where the blue color representing the water area is half, the ratio of invalid color is 50% and the ratio of invalid order is also 50%. These 50% of invalid orders need to be allocated to other active grids.

Flow charts are used herein to illustrate operations performed by systems according to embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, various steps may be processed in reverse order or simultaneously. At the same time, other operations are either added to or removed from these processes.

Fig. 9 is a system hardware implementation environment of regional order analysis according to an embodiment of the present application. The analysis system 900 may include an internal communication bus 901, a Processor (Processor) 902, a Read Only Memory (ROM) 903, a Random Access Memory (RAM) 904, and a communication port 905. When implemented on a personal computer, the analysis system 900 may also include a hard disk 907. The internal communication bus 901 may enable data communication among the components of the analysis system 900. The processor 902 may make the determination and issue the prompt. In some embodiments, the processor 902 may be comprised of one or more processors. The communication port 905 may enable the analysis system 900 to communicate data externally. In some embodiments, the analysis system 900 may send and receive information and data from a network through the communication port 905. The analysis system 900 may also include various forms of program storage units and data storage units, such as a hard disk 907, read Only Memory (ROM) 903 and Random Access Memory (RAM) 904, capable of storing various data files used in computer processing and/or communications, as well as possible program instructions executed by the processor 902. The processor executes these instructions to carry out the main parts of the method. The results processed by the processor are communicated to the user device through the communication port and displayed on the user interface.

The method for analyzing the regional order may be implemented as a computer program, stored in the hard disk 907, and recorded in the processor 902 for execution, so as to implement the method for analyzing the regional order of the present application.

The present application also provides a computer readable medium having stored thereon computer program code which, when executed by a processor, implements a regional order analysis method as described above.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing disclosure is by way of example only, and is not intended to limit the present application. Various modifications, improvements and adaptations to the present application may occur to those skilled in the art, although not explicitly described herein. Such alterations, modifications, and improvements are intended to be suggested herein and are intended to be within the spirit and scope of the exemplary embodiments of this application.

Also, this application uses specific language to describe embodiments of the application. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the present application is included in at least one embodiment of the present application. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the present application may be combined as appropriate.

Aspects of the present application may be embodied entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or in a combination of hardware and software. The above hardware or software may be referred to as "data block," module, "" engine, "" unit, "" component, "or" system. The processor may be one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital signal processing devices (DAPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, or a combination thereof. Furthermore, aspects of the present application may be represented as a computer product, including computer readable program code, embodied in one or more computer readable media. For example, computer-readable media can include, but are not limited to, magnetic storage devices (e.g., hard disk, floppy disk, magnetic strips … …), optical disks (e.g., compact Disk (CD), digital Versatile Disk (DVD) … …), smart cards, and flash memory devices (e.g., card, stick, key drive … …).

The computer readable medium may comprise a propagated data signal with the computer program code embodied therein, for example, on a baseband or as part of a carrier wave. The propagated signal may take any of a variety of forms, including electromagnetic, optical, and the like, or any suitable combination. The computer readable medium can be any computer readable medium that can communicate, propagate, or transport the program for use by or in connection with an instruction execution system, apparatus, or device. Program code on a computer readable medium may be propagated over any suitable medium, including radio, electrical cable, fiber optic cable, radio frequency signals, or the like, or any combination of the preceding.

Similarly, it should be noted that in the preceding description of embodiments of the application, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to imply that more features are required than are expressly recited in the claims. Indeed, the embodiments may be characterized as having less than all of the features of a single disclosed embodiment.

Numerals describing the number of components, attributes, etc. are used in some embodiments, it being understood that such numerals used in the description of the embodiments are modified in some instances by the use of the modifier "about", "approximately" or "substantially". Unless otherwise indicated, "about", "approximately" or "substantially" indicates that the number allows a variation of ± 20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximations that may vary depending upon the desired properties of the individual embodiments. In some embodiments, the numerical parameter should take into account the specified significant digits and employ a general digit preserving approach. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the range are approximations, in the specific examples, such numerical values are set forth as precisely as possible within the scope of the application.

Although the present application has been described with reference to the present specific embodiments, it will be appreciated by those skilled in the art that the above embodiments are merely illustrative of the present application and that various equivalent changes or substitutions may be made without departing from the spirit of the application, and therefore, it is intended that all changes and modifications to the above embodiments within the spirit of the application fall within the scope of the claims of the application.

Claims

1. A regional order analysis method, comprising the steps of:

acquiring a plurality of orders, wherein the orders do not contain latitude and longitude information;

acquiring city grid information according to city map data, wherein the city grid information comprises a plurality of city grids;

establishing a city order distribution model, and generating longitude and latitude information of each order in the plurality of orders by using the city order distribution model; the step of establishing the city order distribution model comprises the following steps: establishing a real city order distribution model as a target model by using actual data; giving a rough order distribution range; calculating a rough model of the urban order distribution model in the order distribution range by using a fitting algorithm, comparing the rough model with the target model, adjusting parameters of the rough model according to a comparison result until the rough model is consistent with the target model, and outputting an optimal urban order distribution model; wherein the step of generating latitude and longitude information for each of the plurality of orders using the city order distribution model comprises: drawing a concentric circle by taking the coordinates of the store as a central point and the boundary value of the distribution distance as a radius; randomly generating a coordinate point in the area covered by the concentric circles and giving an order;

judging the city grid in which each order falls according to the longitude and latitude information of each order;

associating a city grid with one or more orders falling within the city grid; and

order data of an area composed of a plurality of city grids is calculated.

2. The method of claim 1, wherein the step of obtaining city grid information from city map data comprises:

drawing a grid at a plurality of coordinate points in the city map data;

and converting the plane coordinate system of the urban map data into a curved surface coordinate system, and converting the longitude and latitude information in the urban map data into real coordinate information.

3. The method of claim 1, wherein the step of determining the city grid into which each order falls according to the longitude and latitude information of each order comprises:

converting the latitude and longitude information into a geohash value through a geohash algorithm;

generating a grid set stored in the urban grid process through the query of the geohash value;

and judging the grid in which the longitude and latitude information is positioned by a ray method.

4. The method of claim 1, wherein the city grid comprises an active city grid and an inactive city grid, and when the city grid into which each order falls is determined according to the longitude and latitude information of each order, the method further comprises:

when the longitude and latitude information of the order falls into the invalid city grid, redistributing the city grid into which the order falls;

and when the longitude and latitude information of the order falls into the effective city grid, establishing the association between the order and the effective city grid.

5. The method of claim 4, wherein the step of reallocating the city grid into which the order falls comprises:

selecting urban grids of a plurality of circles around the invalid urban grid, and sequentially reducing the urban grids according to the priorities from the inner circle to the outer circle;

and if the first circle contains the effective city grids, the order is averagely distributed to the effective city grids, if the first circle does not contain the effective city grids, the second circle is taken, and the like, and if the last circle still contains no effective city grids, the order is lost.

6. The method of claim 4, wherein the step of obtaining city grid information from the city map data comprises marking invalid city grids in the city map data using invalid region color chips.

7. An area order analysis system comprising:

a memory for storing instructions executable by the processor; and

a processor for executing the instructions to implement the method of any of claims 1-6.

8. A computer-readable medium having stored thereon computer program code which, when executed by a processor, implements the method of any of claims 1-6.