CN112836978B

CN112836978B - Data processing method, device, equipment, medium and product

Info

Publication number: CN112836978B
Application number: CN202110172856.7A
Authority: CN
Inventors: 谢书昭
Original assignee: Beijing Didi Infinity Technology and Development Co Ltd
Current assignee: Beijing Didi Infinity Technology and Development Co Ltd
Priority date: 2021-02-08
Filing date: 2021-02-08
Publication date: 2024-06-04
Anticipated expiration: 2041-02-08
Also published as: CN112836978A

Abstract

The application provides a data processing method, a device, equipment, a medium and a product, wherein the method comprises the following steps: acquiring a first historical required supply ratio and a first historical resource acquisition efficiency of a plurality of days in a target area; in response to determining that the first historical resource acquisition efficiency varies with the first historical demand-to-supply ratio for a plurality of days, and the variation of the first historical resource acquisition efficiency is smaller than a preset threshold, determining a target demand-to-supply ratio according to the first historical demand-to-supply ratio and the first historical resource acquisition efficiency for a plurality of days; and if the current time is within the target time period, determining the adjustment quantity of the service duration of the driver at the current time according to the target required supply ratio and the passenger issuing quantity at the current time.

Description

Data processing method, device, equipment, medium and product

Technical Field

The present application relates to the field of computer technologies, and in particular, to a data processing method, apparatus, device, medium, and product.

Background

At present, in fast-paced life of people, more and more people select a net about car to go out. For the network taxi driver, in the supply and demand scene of the network taxi, the service duration of one driver is relatively fixed in one day, and the driver generally cannot get out of the vehicle in another time period after getting out of the vehicle in one time period, so that the total service duration of the driver in certain time periods is relatively longer, the total service duration of the driver in certain time periods is relatively shorter, the processing speed of orders in certain time periods is relatively slower, more idle capacity can appear in certain time periods, the utilization rate of capacity resources in the time periods is relatively lower, and the capacity resources in the day are not fully utilized. In addition, in the time period with longer total service duration, the data amount generated by each driver in unit time is generally equal, so that the longer the total service duration is, the larger the data amount to be processed in unit time is, and the ratio of effective data aiming at orders is reduced, thereby reducing the processing efficiency of the effective data, and meanwhile, the ratio of ineffective data processed by hardware is relatively larger, thereby reducing the effective utilization rate of hardware resources.

Disclosure of Invention

In view of the above, the present application aims to provide a data processing method, apparatus, device, medium and product, so as to improve the processing efficiency of effective data and the effective utilization of hardware resources.

In a first aspect, an embodiment of the present application provides a data processing method, including:

Acquiring a first historical demand ratio and a first historical resource acquisition efficiency of a plurality of days in a target area, wherein the first historical demand ratio is determined according to the ratio of the historical ticket sending amount of passengers in the target area in a target time period of the day to the historical service duration of a driver, and the first historical resource acquisition efficiency is determined according to the ratio of the historical resource acquisition amount of the drivers in the target time period of the day to the historical service duration of the drivers;

In response to determining that the first historical resource acquisition efficiency varies with the first historical demand-to-supply ratio for a plurality of days, and the variation of the first historical resource acquisition efficiency is smaller than a preset threshold, determining a target demand-to-supply ratio according to the first historical demand-to-supply ratio and the first historical resource acquisition efficiency for a plurality of days;

and if the current time is within the target time period, determining the adjustment quantity of the service duration of the driver in the current time according to the target required supply ratio and the passenger order issuing quantity in the current time.

In a second aspect, an embodiment of the present application provides a data processing apparatus, including:

An obtaining unit, configured to obtain a first historical demand ratio and a first historical resource obtaining efficiency of a plurality of days in a target area, where the first historical demand ratio is determined according to a ratio of a historical ticket amount of a passenger in a target time period of the target area in the day to a historical service duration of a driver, and the first historical resource obtaining efficiency is determined according to a ratio of a historical resource obtaining amount of the driver in the target time period of the target area in the day to the historical service duration of the driver;

A first determining unit, configured to determine a target demand-to-supply ratio according to the first historical demand-to-supply ratio and the first historical resource acquisition efficiency for a plurality of days, in response to determining that the first historical resource acquisition efficiency for a plurality of days varies with the first historical demand-to-supply ratio, and that a variation of the first historical resource acquisition efficiency is smaller than a preset threshold;

And the second determining unit is used for determining the adjustment amount of the service duration of the driver at the current time according to the target required supply ratio and the passenger order issuing amount at the current time if the current time is within the target time period.

In a third aspect, an embodiment of the present application provides an electronic device, including: a processor, a storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating over a bus when the electronic device is running, the processor executing the machine-readable instructions to perform the steps of the method as described in the first aspect.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method as described in the first aspect.

In a fifth aspect, embodiments of the present application provide a computer program product comprising computer programs/instructions which, when executed by a processor, implement the steps of the method.

The technical scheme provided by the embodiment of the application can comprise the following beneficial effects:

In the application, first historical demand ratio and first historical resource acquisition efficiency of a plurality of days in a target area are firstly acquired, the ratio of the historical ticket quantity of passengers in a target time period of each history in the target area to the historical service time length of a driver can be determined through the first historical demand ratio, the ratio of the historical resource acquisition quantity of the drivers in the target time period of each history in the target area to the historical service time length of the drivers can be determined through the first historical resource acquisition efficiency, the first data group which belongs to the same day and can be formed by the first historical demand ratio and the first historical resource acquisition efficiency can be determined through comparing the data groups of a plurality of days, and therefore, when the first historical demand ratio changes along with the first historical demand ratio, the change quantity of the first historical resource acquisition efficiency is smaller than the target demand ratio when the first historical resource acquisition efficiency is smaller than a preset threshold value, namely: the method can determine the corresponding supply and demand ratio when the resource acquisition efficiency of the driver reaches the upper limit in the target time period, so the proportional relation between the order quantity of the passengers and the service time of the driver in the current time period can be determined through the target supply and demand ratio, when the current time is in the target time period, the adjustment quantity of the service time of the driver in the current time period can be determined according to the obtained target supply and the passenger order quantity of the current time, therefore, the adjustment quantity of the service time of the driver in different time periods can be determined through the method, the service time of the driver in different time periods can be adjusted after the adjustment quantity is determined, after the service time of the driver in different time periods is adjusted according to the adjustment quantity, the supply and demand conditions in each time period of the current time period are close to balance, the order processing speed in each time period of the current time period is favorably improved, idle capacity in each time period is favorably reduced, the utilization rate of the current time carrying capacity is favorably improved, and the data in the current time period is favorably processed in the current time period, the time period is favorably, the data in the current time period is favorably obtained, the data is favorably obtained by the driver, the data in the time period is favorably being correspondingly increased, the time period is favorably, the time of the current in the time period is favorably occupied by the time period, and the data is favorably being adjusted, the time is favorably in the time, the time is favorably is greatly increased, and the time is favorably is in the time, thereby being beneficial to improving the effective utilization rate of hardware resources.

In order to make the above objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a flow chart of a data processing method according to a first embodiment of the present application;

FIG. 2 is a flowchart of another data processing method according to a first embodiment of the present application;

FIG. 3 is a flowchart illustrating another data processing method according to a first embodiment of the present application;

FIG. 4 is a schematic view of a scatter division according to a first embodiment of the present application;

FIG. 5 is a flowchart illustrating another data processing method according to a first embodiment of the present application;

Fig. 6 is a schematic diagram of a line segment constructed by coordinates of a scatter gather according to a first embodiment of the present application;

FIG. 7 is a flowchart of another data processing method according to a first embodiment of the present application;

FIG. 8 is a flowchart illustrating another data processing method according to a first embodiment of the present application;

FIG. 9 is a flowchart of another data processing method according to a first embodiment of the present application;

FIG. 10 is a flowchart of another data processing method according to a first embodiment of the present application;

FIG. 11 is a schematic diagram of a data processing apparatus according to a second embodiment of the present application;

FIG. 12 is a schematic diagram of another data processing apparatus according to a second embodiment of the present application;

fig. 13 is a schematic structural diagram of an electronic device according to a third embodiment of the present application.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present application, and it should be understood that the drawings in the present application are for the purpose of illustration and description only and are not intended to limit the scope of the present application. In addition, it should be understood that the schematic drawings are not drawn to scale. A flowchart, as used in this disclosure, illustrates operations implemented according to some embodiments of the present application. It should be understood that the operations of the flow diagrams may be implemented out of order and that steps without logical context may be performed in reverse order or concurrently. Moreover, one or more other operations may be added to or removed from the flow diagrams by those skilled in the art under the direction of the present disclosure.

In addition, the described embodiments are only some, but not all, embodiments of the application. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.

In order to enable those skilled in the art to use the present disclosure, the following embodiments are given in connection with a specific application scenario "supply and demand scenario of network about cars". It will be apparent to those having ordinary skill in the art that the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the application. While the present application is primarily described in terms of a supply and demand scenario for a net cart, it should be understood that this is but one exemplary embodiment.

It should be noted that the term "comprising" will be used in embodiments of the application to indicate the presence of the features stated hereafter, but not to exclude the addition of other features.

The terms "passenger," "requestor," "service requestor," and "customer" are used interchangeably herein to refer to a person, entity, or tool that may request or subscribe to a service. The terms "driver," "provider," "service provider," and "provider" are used interchangeably herein to refer to a person, entity, or tool that can provide a service. The term "user" in the present application may refer to a person, entity or tool requesting, subscribing to, providing or facilitating the provision of a service. For example, the user may be a passenger, driver, operator, etc., or any combination thereof. In the present application, "passenger" and "passenger terminal" may be used interchangeably, and "driver" and "driver terminal" may be used interchangeably.

The terms "service request" and "order" are used interchangeably herein to refer to a request initiated by a passenger, service requester, driver, service provider, or vendor, etc., or any combination thereof. Accepting the "service request" or "order" may be a passenger, a service requester, a driver, a service provider, a vendor, or the like, or any combination thereof. The service request may be either fee-based or free.

It should be noted in advance that, in the present application, when the resource acquisition efficiency of the driver reaches the upper limit, the proportional relationship between the number of orders issued by the passenger and the service duration of the driver may be used as the proportional relationship when the supply and demand are balanced, where the service duration of the driver refers to the duration when the driver is in the service state, that is: after a driver logs in the network vehicle-restraining platform, the driver can be in a vehicle-out state through setting operation, the driver can listen to a bill, receive the bill and the like when in the vehicle-out state, and the driver can bear passengers to go to a destination after receiving the bill, and the duration of the driver when in the vehicle-out state is the service duration of the driver.

It should be noted that, in the present application, the demand ratio and the resource obtaining efficiency with the correspondence relation refer to the demand ratio and the resource obtaining efficiency in a certain period of time, for example: the demand ratio and the resource acquisition efficiency having a correspondence relationship in the day refer to the demand ratio corresponding to the day, which is determined from the ratio of the total number of orders generated in the day by all passengers in the specified area and the total service duration in the day by all drivers in the specified area, and the resource acquisition efficiency corresponding to the day, which is determined from the ratio of the total resource acquisition amount in the day by all drivers in the specified area and the total service duration in the day by all drivers in the specified area.

The resource acquisition efficiency of the driver is changed along with the change of the demand ratio of the driver, when the demand ratio is within a certain range, the number of orders received by the driver in unit time is increased, so that the resource acquisition efficiency of the driver can be improved, but when the demand ratio exceeds the range, the order making time of the driver is full, so that the resource acquisition efficiency of the driver reaches the upper limit.

For the supply and demand scenes of the network about cars, in some time periods, the demand is more but the idle capacity is less, in some time periods, the demand is less but the idle capacity is more, and in any case, the situation of unbalanced supply and demand is caused, so that the processing speed of orders in some time periods is relatively slower, and in some time periods, more idle capacity can appear, so that the utilization rate of capacity resources in the time periods is relatively lower, the capacity resources in the day are not fully utilized, and the resource acquisition efficiency of drivers cannot be as much as possible near the upper limit. If the service duration of the driver in the time period with unbalanced supply and demand can be adjusted, the supply and demand conditions of each time period in the same day can be balanced, so that the processing speed of orders in each time period is relatively high, the capacity resources in each time period are fully utilized, and meanwhile, the resource acquisition efficiency of the driver as many as possible can be close to the upper limit.

In order to solve the above problems, the present application provides a data processing method, apparatus, device, medium and product, and the following is a detailed description of the present application.

Example 1

Fig. 1 is a flow chart of a data processing method according to a first embodiment of the present application, as shown in fig. 1, the method includes the following steps:

Step 101, acquiring a first historical demand ratio and a first historical resource acquisition efficiency of a plurality of days in a target area, wherein the first historical demand ratio is determined according to the ratio of the historical ticket amount of a passenger in the target area in a target time period of the day to the historical service duration of a driver, and the first historical resource acquisition efficiency is determined according to the ratio of the historical resource acquisition amount of the driver in the target time period of the day to the historical service duration of the driver.

Specifically, the historical demand ratio and the historical resource acquisition efficiency with corresponding relations in history can reflect the demand ratio corresponding to the resource acquisition efficiency when the historical demand ratio reaches the upper limit, and the application is used for determining the capacity adjustment quantity of different time periods in the same day, so that the historical demand ratio and the historical resource acquisition efficiency of a target area in different time periods in each day (the daily of the target area in the historical time period is the time period of the history) can be acquired, the first historical demand ratio and the first historical resource acquisition efficiency of the target area in the target time period in each day can be obtained, the historical time period is taken as 30 days for example, the historical day is divided into 5 time periods (for example, the early peak time period is 23 to 6 points, the early peak time period is 7 to 9 points, the peak time period is 10 to 16 points, the late peak time period is 17 to 19 points, and the night peak time period is 20 to 22 points), and when the early morning time period is taken as the target time period, the first historical demand ratio and the first historical demand ratio with corresponding relations between the first demand ratio and the first historical resource acquisition efficiency can be obtained.

It should be noted that, the historical demand ratio and resource acquisition efficiency in different time periods each day may be determined by using the order information generated by the passengers, the order information generated by the drivers, and the on-line information of the drivers, for example: when the demand ratio and the resource acquisition efficiency of the early morning time period are determined, the order sending quantity of the passengers in the early morning time period can be determined according to order information generated by the passengers in the early morning time period in the day, the resource acquisition quantity of the drivers in the early morning time period is determined according to order receiving information generated by the drivers in the early morning time period in the day, the service duration of the drivers in the early morning time period can be determined according to the on-line information of the drivers in the early morning time period in the day, and the demand ratio and the resource acquisition efficiency of the drivers in the early morning time period in the day can be determined according to the three information.

Step 102, in response to determining that the first historical resource acquisition efficiency varies with the first historical demand-to-supply ratio for a plurality of days, and the variation of the first historical resource acquisition efficiency is smaller than a preset threshold, determining a target demand-to-supply ratio according to the first historical demand-to-supply ratio and the first historical resource acquisition efficiency for a plurality of days.

Specifically, after the first historical demand ratio and the first historical resource acquisition efficiency of multiple days in the target time period are obtained, how the first historical resource acquisition efficiency changes along with the change of the first historical demand ratio in the target time period can be determined according to the obtained first historical demand ratio and the first historical resource acquisition efficiency, so that the first historical resource acquisition efficiency basically does not change when the first historical demand ratio is large in the target time period, namely: the target supply-demand ratio corresponding to the driver's resource acquisition efficiency reaching the upper limit in the target time period can be determined, and after the target supply-demand ratio is determined, even if the first historical supply-demand ratio is increased, the variation of the first historical resource acquisition efficiency is relatively smaller, and at this time, the variation of the first historical resource acquisition efficiency is smaller than a preset threshold.

After the obtained first historical demand-to-supply ratio and the first historical resource obtaining efficiency, the target demand-to-supply ratio may be determined according to the distribution direction of the data set formed by the first historical demand-to-supply ratio and the first historical resource obtaining efficiency having the correspondence relationship, or may be obtained by performing linear fitting according to the distribution data of the data set formed by the first historical demand-to-supply ratio and the first historical resource obtaining efficiency having the correspondence relationship, and then analyzing the slope of the fitting dotted line obtained after the linear fitting.

Step 103, if the current time is within the target time period, determining an adjustment amount of the service duration of the driver in the current time according to the target required supply ratio and the passenger order issuing amount in the current time.

Specifically, after the target demand ratio is obtained, the corresponding supply-demand ratio when the resource obtaining efficiency of the driver reaches the upper limit in the target time period can be determined, so that the proportional relationship between the order sending amount of the passenger and the service duration of the driver in the target time period can be determined through the target demand ratio, and when the current time is in the target time period, the adjustment amount of the service duration of the driver in the current time can be determined by utilizing the order sending amount of the passenger in the current time and the determined target demand ratio, for example: the optimal online time length of the driver in the target time period of the target area can be determined through the target required supply ratio and the passenger order sending amount in the current time, and the service time length of the target area in the current time can be determined through the online information of the driver, so that the obtained optimal online time length and the service time length in the current time can be utilized to determine the adjustment amount of the service time length of the driver in the current time, for example: the service duration of the driver in the target area at the current time is reduced, or the service duration of the driver in the target area at the current time is increased.

The method can determine the adjustment quantity of the service time length of the drivers in different time periods every day, and can adjust the service time length of the drivers in different time periods every day after the adjustment quantity is determined, after the adjustment of the service time length of the drivers in different time periods every day according to the adjustment quantity, the supply and demand conditions in each time period of the day are balanced, thereby being beneficial to improving the order processing speed in each time period of the day, reducing the idle capacity in each time period of the day, and further being beneficial to improving the utilization rate of the current capacity resources, and because the target supply and demand ratio is the supply and demand ratio corresponding to the time when the resource acquisition efficiency of the drivers in the target time period reaches the upper limit, the resource acquisition efficiency of the drivers in different time periods of the day is beneficial to be close to the upper limit after the adjustment of the service time length of the drivers in different time periods of the day according to the adjustment quantity. In addition, the total service duration in each time period can be relatively suitable through the method, so that the data quantity generated by a driver in unit time can be reduced, the duty ratio of effective data for orders can be increased, the processing speed of the effective data can be increased, and meanwhile, the duty ratio of the effective data processed by hardware is increased, so that the effective utilization rate of hardware resources can be increased.

The required supply ratio corresponding to the case where the resource obtaining efficiency of the driver reaches the upper limit is the required supply ratio corresponding to the case where the supply and the demand are balanced.

In a possible implementation manner, fig. 2 is a schematic flow chart of another data processing method according to the first embodiment of the present application, as shown in fig. 2, when step 102 is performed, the following steps may be implemented:

Step 201, determining coordinates of scattered points formed by the first historical demand-supply ratio and the first historical resource acquisition efficiency belonging to the same day.

And 202, determining a target point with the distribution trend of the scattered points changed according to the coordinates of the scattered points, and taking the required supply ratio corresponding to the target point as the target required supply ratio.

Specifically, after the first historical demand ratio and the first historical resource acquisition efficiency of each day in the target time period in the history are obtained, the first historical demand ratio can be used as an abscissa, and the first historical resource acquisition efficiency is used as an ordinate, so that the first historical demand ratio and the first historical resource acquisition efficiency belonging to the same day form a scattered point, a plurality of scattered points corresponding to a plurality of days can be obtained through the method, the change condition of the first historical resource acquisition efficiency along with the increase of the first historical demand ratio can be determined through the coordinates of the scattered points, when the first historical demand ratio is increased to a certain extent, the change amount of the first historical resource acquisition efficiency is relatively smaller, and at the moment, the first historical resource acquisition efficiency reaches an upper limit, so that the target point when the distribution trend of the scattered points changes can be determined according to the coordinates of the scattered points, namely: the method comprises the steps that when the change quantity of the first historical resource acquisition efficiency does not change greatly along with the increase of the first historical demand ratio, the corresponding resource acquisition efficiency of the target point is the resource acquisition efficiency of which the first historical resource acquisition efficiency reaches the upper limit in the increase process, after the target point is obtained, the demand ratio corresponding to the target point can be used as the target demand ratio, so that the adjustment quantity of the service duration of a driver at the current time can be determined according to the target demand ratio, the distribution trend situation of scattered points can be directly and conveniently determined through the coordinates of the scattered points, and the target point can be determined more accurately.

In a possible implementation manner, fig. 3 is a schematic flow chart of another data processing method according to the first embodiment of the present application, as shown in fig. 3, when step 202 is performed, the method may be implemented by the following steps:

step 301, sorting the first historical demand ratios corresponding to each day in the target time period according to a designated sequence, and obtaining a sorting result.

Step 302, uniformly dividing the sorting result into a preset number of candidate sets.

And 303, determining a target set with the largest distribution trend change of the scattered points according to the coordinates of the scattered points corresponding to each candidate set.

And 304, determining the target point according to the coordinates of the scattered points corresponding to the target set.

Specifically, in the process that the first history resource obtaining efficiency changes along with the change of the first history demand-to-supply ratio, the distribution trend of the scattered points only changes greatly at the position of the target point, for example: at the beginning, the first historical resource acquisition efficiency increases along with the increase of the first historical demand ratio, the variation of the first historical resource acquisition efficiency is obvious, the first historical resource acquisition efficiency does not change along with the increase of the first historical demand ratio after reaching the target point, at the moment, the variation of the first historical resource acquisition efficiency is relatively small, that is, the inflection point of the variation of the first historical resource acquisition efficiency is positioned at the target point, in order to reduce the calculation amount, a section of area where the target point is positioned can be selected for analysis to determine the target point, so that the first historical demand ratio corresponding to each day in the target period can be ordered in order from small to large or from large to small, then the ordering result is evenly divided to obtain a preset number of candidate sets, at the moment, each candidate set comprises the same number of scattered points, and the value range of the abscissa corresponding to each candidate set can be determined by the abscissa of the corresponding scatter point of the candidate set, fig. 4 is a schematic view of scatter point division provided in the first embodiment of the present application, as shown in fig. 4, the scatter points can be divided into three parts in the above manner, the differences between the maximum abscissa and the minimum abscissa corresponding to different candidate sets may be different, but the number of the scatter points included in different candidate sets is the same, and as shown in fig. 4, the distribution trend of the scatter point corresponding to the candidate set on the left side is an ascending change, the distribution trend of the scatter point corresponding to the candidate set on the right side is substantially steady, the distribution trend of the scatter point corresponding to the candidate set on the middle is turned from the ascending trend to steady, at this time, it may be determined that the distribution trend of the scatter point corresponding to the candidate set on the middle is the largest, in this case, the candidate set located in the middle is set as the target, then the target point is determined according to the coordinates of the scattered points corresponding to the target set, and the calculation amount is reduced when the target scattered points are determined again in the above manner.

In a possible implementation manner, fig. 5 is a schematic flow chart of another data processing method according to the first embodiment of the present application, as shown in fig. 5, when step 303 is executed, the method may be implemented by the following steps:

Step 501, sequentially numbering the candidate sets according to the order from small to large.

Step 502, calculating an average value of the first historical resource acquisition efficiency corresponding to the first historical demand ratios included in each candidate set.

Step 503, for each candidate set, determining coordinates of a scatter point set formed by the number of the candidate set and an average value corresponding to the candidate set.

And 504, determining a target set according to the coordinates of the scattered point set, wherein the target set is the scattered point set which is included by two adjacent oblique line segments with the largest gradient difference, and the oblique line segments are formed by coordinates of two adjacent scattered point sets.

Specifically, after the candidate sets are obtained, each candidate set corresponds to a different value range, and the scattered points included in each candidate set are distributed in the scattered point distribution diagram according to the size order of the value ranges, so that each candidate set can be sequentially numbered according to the order in which the candidate sets arrive from small, for example: when the candidate sets include 5, numbering the candidate sets with 1,2, 3, 4 and 5 sequentially according to the order of the candidate sets from small to large, calculating an average value of the first historical resource acquisition efficiency corresponding to the first historical supply ratio included in each candidate set, then taking the number of each candidate set as an abscissa, taking the average value of each candidate set as an ordinate, constructing coordinates of each scattered point set, and reflecting the change condition of the first historical resource acquisition efficiency corresponding to the corresponding candidate set through the average value, for example: the average value corresponding to the plurality of candidate sets still increases in the increasing stage of the first historical resource obtaining efficiency, the average value corresponding to the plurality of candidate sets has relatively smaller phase difference in the plurality of candidate sets corresponding to the stationary stage of the first historical resource obtaining efficiency, and the average value corresponding to the candidate set is larger than the average value corresponding to the increasing stage and smaller than the average value corresponding to the stationary stage when the first historical resource obtaining efficiency reaches the upper limit, so that the distribution trend of the coordinates of the scattered point sets can represent the change condition of the first historical resource obtaining efficiency corresponding to each candidate set, namely: the first historical resource obtaining efficiency corresponding to each candidate set changes along with the increase of the candidate set, and further, the distribution trend of coordinates of the scatter sets can be determined to have larger change in which candidate set the distribution trend of the scatter has occurred, fig. 6 is a schematic diagram of a line segment constructed by coordinates of the scatter sets, as shown in fig. 6, when determining a target set, firstly constructing a diagonal segment formed by points corresponding to coordinates of adjacent scatter sets, then determining a slope difference of slopes between two adjacent diagonal segments, and then determining two diagonal segments with the largest slope difference, so that the scatter sets included by the two diagonal segments are used as the target set, and the target point is located in a horizontal coordinate section where the target set is located.

In a possible implementation manner, fig. 7 is a schematic flow chart of another data processing method according to the first embodiment of the present application, as shown in fig. 7, and on the basis of the content shown in fig. 5, when step 304 is performed, the following steps may be implemented:

And 701, uniformly dividing intervals formed by the maximum value and the minimum value of the first history required supply ratio in the target set according to the preset number to obtain a corresponding number of dividing points.

And step 702, for each dividing point, dividing the scattered points between the maximum value and the minimum value by using the value corresponding to the dividing point to obtain a first scattered point set and a second scattered point set which are used for representing the two sides of the dividing point.

Step 703, determining a distribution difference value of the first scatter point set corresponding to the dividing point and the second scatter point set corresponding to the dividing point according to the coordinates of the first scatter point set corresponding to the dividing point and the coordinates of the second scatter point set corresponding to the dividing point.

Step 704, determining a maximum distribution difference value in the distribution difference values corresponding to the division points.

Step 705, determining the target point according to the coordinates of the dividing point corresponding to the maximum distribution difference value and the scattered point corresponding to the target set.

Specifically, in order to determine a relatively accurate target point, a section formed by a maximum value and a minimum value of a first history required to be supplied in a target set may be uniformly divided according to a preset number to obtain a corresponding number of dividing points, and then a scattered point located between the maximum value and the minimum value is divided by using a value corresponding to each dividing point to obtain a first scattered point set and a second scattered point set used for representing positions on two sides of the dividing point, namely: for each dividing point, dividing a distribution graph of the scattering points corresponding to the target set by using a numerical value corresponding to the dividing point to obtain a first scattering point set and a second scattering point set which are positioned at two sides of the dividing point, obtaining multiple groups of the first scattering point set and the second scattering point set through the method, respectively determining linear distribution trend of the first scattering point set and linear distribution trend of the second scattering point set in the group of scattering point sets for each group of scattering point sets, and determining distribution difference values of the first scattering point set and the second scattering point set in the group of scattering point sets by comparing the two linear distribution trend, wherein the distribution difference values of the first scattering point set and the second scattering point set obtained when the target point is taken as the dividing point are maximum, so that the distribution difference value corresponding to the dividing point of the maximum distribution difference value is larger on the abscissa, which is closer to the target point (the coordinate corresponding to the first history resource obtaining efficiency reaches the upper limit), and then taking the numerical value corresponding to the dividing point of the maximum distribution difference value as the abscissa of the target point after determining the maximum distribution value, and then determining the complete distribution difference value of the target point corresponding to the target point.

It should be noted that, the specific value of the preset number may be set according to the actual required accuracy of the target point, where the greater the preset number, the higher the accuracy of the obtained target point.

In a possible implementation manner, fig. 8 is a schematic flow chart of another data processing method according to the first embodiment of the present application, as shown in fig. 8, and in performing step 703, the method may be implemented by the following steps:

Step 801, performing linear regression fit on the first scatter set and the second scatter set respectively to obtain a first line segment corresponding to the first scatter set and a second line segment corresponding to the second scatter set.

Step 802, calculating a mean value of goodness of fit of the first line segment and the second line segment, and taking the mean value as the distribution difference value.

Specifically, for each group of scattered point sets, linear fitting is respectively carried out on a first scattered point set and a second scattered point set in the group of scattered point sets, so that a fitted line segment (namely, a first line segment) of the first scattered point set and a fitted line segment (second line segment) of the second scattered point set are obtained, wherein the first line segment can represent the trend situation of scattered point distribution of the first scattered point set in the group of scattered point sets, the second line segment can represent the trend situation of scattered point distribution of the second scattered point set in the group of scattered point sets, then the mean value of the fitting goodness of the first line segment and the second line segment is calculated, wherein the larger the mean value of the fitting goodness is used for representing that the distribution trend of the first scattered point set and the distribution trend of the second scattered point set are different, namely, the dividing point is closer to a target point, and therefore, after taking the mean value of the fitting goodness is taken as a distribution difference value, the mean value of the largest fitting goodness is used for determining a relatively accurate target point.

In a possible implementation manner, fig. 9 is a schematic flow chart of another data processing method according to the first embodiment of the present application, as shown in fig. 9, and when step 705 is performed on the basis of the content shown in fig. 8, the following steps may be implemented:

step 901, determining the maximum average value of the average values of the goodness of fit corresponding to the dividing points.

Step 902, determining an intersection point of a straight line where the dividing point corresponding to the maximum average value is located and a target line segment, and taking the intersection point as the target point, wherein the target line segment comprises a first line segment and a second line segment corresponding to the maximum average value.

Specifically, after determining the dividing point corresponding to the maximum average value in the average value of the fitting goodness, the value M corresponding to the dividing point may be used as the abscissa, a straight line perpendicular to the abscissa and located at the M position of the intersection point with the abscissa may be constructed, the first line segment and the second line segment corresponding to the maximum average value in the average value of the fitting goodness may be obtained through the content shown in fig. 8, and then the intersection point of the first line segment and the second line segment and the straight line may be determined, and the intersection point may be used as the target point, so that the relatively accurate target point may be obtained through the above method.

In a possible implementation manner, fig. 10 is a schematic flow chart of another data processing method according to the first embodiment of the present application, as shown in fig. 10, when step 103 is performed, the following steps may be implemented:

Step 1001, obtaining a second historical demand ratio in the target area in the target time period.

Step 1002, calculating a difference between the target demand-to-supply ratio and the second historical demand-to-supply ratio to obtain a demand-to-supply ratio difference.

Step 1003, determining the adjustment amount according to the ratio of the passenger order amount at the current time to the required supply ratio difference value.

Specifically, a second historical demand-to-supply ratio of the target time period in the target area is obtained, and the ratio of the total number of passengers issued by the target area in the target time period to the total service duration of the driver in the last period can be determined through the second historical demand-to-supply ratio, for example: the method comprises the steps of determining the total order sending amount of the last 7 days and the total service time length of the last 7 days in a target time period, determining a second historical demand ratio according to the ratio of the total order sending amount of the last 7 days and the total service time length of the last 7 days, comparing the target demand ratio with the second historical demand ratio to obtain a difference value, determining whether the service time length of a driver in the target time period of the target area is matched with the order number, when the difference value is positive, indicating that the service time length of the driver in the target time period of the target area cannot meet the demand of the order, when the difference value is negative, indicating that the service time length of the driver in the target time period of the target area exceeds the demand of the order, and assuming that the order sending amount of a passenger in the target area cannot change, in order obtaining efficiency of the driver in the target time period of the target area is as close as possible to the corresponding resource obtaining efficiency, calculating the ratio of the passenger order sending amount in the current time period of the target area and the demand ratio difference value, determining the service adjustment amount of the driver in the current time period, and adjusting the service time length of the driver in the target time period of the target area according to the adjustment amount, thereby being beneficial to increasing the service time length of the driver in the target time period of the target area. And after the service time length of the driver in different time periods of the day is adjusted according to the adjustment amount, the supply and demand conditions in each time period of the day are enabled to be close to balance, so that order processing speed in each time period of the day is improved, idle transport capacity in each time period of the day is reduced, and utilization rate of transport capacity resources of the day is improved. In addition, the total service duration in each time period can be relatively suitable through the method, so that the data quantity generated by a driver in unit time can be reduced, the duty ratio of effective data for orders can be increased, the processing speed of the effective data can be increased, and meanwhile, the duty ratio of the effective data processed by hardware is increased, so that the effective utilization rate of hardware resources can be increased.

It should be noted that, after obtaining the target demand ratio and the passenger order amount at the current time, the adjustment amount of the service duration of the driver at the current time may also be determined by other manners, for example: the service duration of the driver at the current time is obtained, the target service duration is calculated by the target required supply ratio and the passenger issuing unit at the current time, then the adjustment amount is determined according to the difference between the target service duration and the service duration of the driver at the current time, or the estimated service duration at the current time can be estimated, the target service duration is calculated by the target required supply ratio and the passenger issuing unit at the current time, then the adjustment amount is determined according to the difference between the target service duration and the estimated service duration at the current time, and the specific mode for determining the adjustment amount is not particularly limited.

In a possible embodiment, after determining the adjustment amount of the target area in the target time period, when the required supply ratio difference is a positive value, increasing the service duration of the driver in the target area at the current time according to the adjustment amount; and when the required supply ratio difference value is a negative value, reducing the service duration of the driver in the target area at the current time according to the adjustment quantity.

In one possible embodiment, after the adjustment amounts corresponding to the respective time periods are obtained, the capacity adjustment information including the time period for which the service duration needs to be increased is transmitted to the target driver including the driver who provides the service fixed in the time period for which the service duration needs to be reduced.

Taking the example that each day is divided into 5 time periods, the service duration needs to be increased in some time periods, and the service duration needs to be reduced in some time periods, so after the adjustment amount corresponding to each time period is determined, the service duration in the time period needing to be reduced in service duration can be transferred to the time period needing to be increased in service duration, and some drivers can get out in a fixed time period, so that the service duration of the drivers getting out in the time period needing to be reduced in service duration can be properly reduced, namely: the driver who gets out of the time slot makes the driver get out of the time slot needing to increase the service time length by a certain means, and after the service time length of the driver in different time slots of the day is adjusted according to the adjustment quantity, the supply and demand conditions in each time slot of the day are close to balance, so that the order processing speed in each time slot of the day is improved, the idle capacity in each time slot of the day is reduced, the utilization rate of the capacity resources of the day is improved, and the income efficiency of the driver who gets out of the vehicle in each time slot is improved. In addition, the total service duration in each time period can be relatively suitable through the method, so that the data quantity generated by a driver in unit time can be reduced, the duty ratio of effective data for orders can be increased, the processing speed of the effective data can be increased, and meanwhile, the duty ratio of the effective data processed by hardware is increased, so that the effective utilization rate of hardware resources can be increased.

It should be noted that, the adjustment strategy for the departure time of the driver may be set according to actual needs, for example: the drivers are classified according to full-time types, wherein the full-time drivers are characterized in that the online time length of nearly 30 days exceeds 9 hours, the full-time drivers are used as network vehicles, the daily fixed departure time length is longer, a single time rule is made, after the fact that the service time length of the drivers needs to be reduced to 1000 hours in the early morning time period is determined, the service time length of the drivers needs to be increased to 1000 hours in the late peak time period, a confirmation popup window is preferentially issued to the full-time drivers with relatively large occupied time in the early morning time period in the evening, the drivers are informed of whether the drivers are willing to contribute the departure time to the late peak time period (the contribution time length can be freely controlled), the total daily departure time length reaches the historical daily average online time length (such as 9 hours) of the drivers, the post is made to reach if the income of the drivers does not reach the historical daily average income, and the specific adjustment strategy is not specifically limited.

Example two

Fig. 11 is a schematic structural diagram of a data processing apparatus according to a second embodiment of the present application, as shown in fig. 11, where the apparatus includes:

An obtaining unit 1101, configured to obtain a first historical demand ratio and a first historical resource obtaining efficiency of a plurality of days in a target area, where the first historical demand ratio is determined according to a ratio of a historical ticket amount of a passenger in a target time period of the target area and a historical service duration of a driver, and the first historical resource obtaining efficiency is determined according to a ratio of a historical resource obtaining amount of a driver in the target time period of the target area and a historical service duration of the driver;

A first determining unit 1102, configured to determine a target demand-to-supply ratio according to the first historical demand-to-supply ratio and the first historical resource acquisition efficiency for a plurality of days, in response to determining that the first historical resource acquisition efficiency for a plurality of days varies with the first historical demand-to-supply ratio, and that a variation of the first historical resource acquisition efficiency is less than a preset threshold;

the second determining unit 1103 is configured to determine, if the current time is within the target time period, an adjustment amount of a service duration of the driver at the current time according to the target demand ratio and the passenger order amount at the current time.

In a possible implementation manner, the first determining unit 1102 is configured to, in response to determining that the first historical resource acquisition efficiency varies with the first historical demand ratio for a plurality of days, and an amount of variation of the first historical resource acquisition efficiency is smaller than a preset threshold, determine a target demand ratio according to the first historical demand ratio and the first historical resource acquisition efficiency for a plurality of days, and include:

Determining coordinates of scattered points formed by the first historical demand-supply ratio and the first historical resource acquisition efficiency belonging to the same day;

And determining a target point with the distribution trend of the scattered points changed according to the coordinates of the scattered points, and taking the required supply ratio corresponding to the target point as the target required supply ratio.

In a possible embodiment, when the first determining unit 1102 is configured to determine, according to the coordinates of the scatter, a target point where the distribution trend of the scatter changes, the method includes:

sequencing the first historical demand ratios corresponding to each day in the target time period according to a specified sequence to obtain a sequencing result;

Uniformly dividing the sequencing result into a preset number of candidate sets;

determining a target set with the largest distribution trend change of the scattered points according to the coordinates of the scattered points corresponding to each candidate set;

and determining the target point according to the coordinates of the scattered points corresponding to the target set.

In a possible embodiment, when the first determining unit 1102 is configured to determine, according to coordinates of the scattered points corresponding to each candidate set, a target set with a largest change in a distribution trend of the scattered points, the method includes:

sequentially numbering the candidate sets according to the sequence from small to large of the candidate sets;

calculating an average value of first historical resource acquisition efficiency corresponding to the first historical demand ratios included in each candidate set;

for each candidate set, determining coordinates of a scattered point set formed by the number of the candidate set and the average value corresponding to the candidate set;

And determining a target set according to the coordinates of the scattered point set, wherein the target set is the scattered point set which is included by two adjacent oblique line segments with the largest gradient difference, and the oblique line segments are composed of the coordinates of every two adjacent scattered point sets.

In a possible embodiment, when the first determining unit 1102 determines the target point according to the coordinates of the scatter points corresponding to the target set, the determining unit includes:

according to the preset number, uniformly dividing intervals formed by the maximum value and the minimum value of the first historical required supply ratio in the target set to obtain a corresponding number of dividing points;

For each dividing point, dividing the scattered points between the maximum value and the minimum value by using a value corresponding to the dividing point to obtain a first scattered point set and a second scattered point set which are used for representing the two sides of the dividing point;

Determining a distribution difference value of the first scattered point set corresponding to the dividing point and the second scattered point set corresponding to the dividing point according to the coordinates of the first scattered point set corresponding to the dividing point and the coordinates of the second scattered point set corresponding to the dividing point;

determining the maximum distribution difference value in the distribution difference values corresponding to the division points;

and determining the target point according to the coordinates of the dividing point corresponding to the maximum distribution difference value and the scattered point corresponding to the target set.

In a possible embodiment, the determining, by the first determining unit 1102, the distribution difference value of the first set of scattering points corresponding to the dividing point and the second set of scattering points corresponding to the dividing point according to the coordinates of the first set of scattering points corresponding to the dividing point includes:

Performing linear regression fit on the first scattered point set and the second scattered point set respectively to obtain a first line segment corresponding to the first scattered point set and a second line segment corresponding to the second scattered point set;

and calculating the average value of the goodness of fit of the first line segment and the second line segment, and taking the average value as the distribution difference value.

In a possible embodiment, the first determining unit 1102 is configured to determine, according to coordinates of a dividing point corresponding to the maximum distribution difference value and a scatter point corresponding to the target set, the target point, where the determining includes:

Determining the maximum average value in the average values of the fitting goodness corresponding to the dividing points;

And determining an intersection point of a straight line where a dividing point corresponding to the maximum average value is located and a target line segment, wherein the target line segment comprises a first line segment and a second line segment corresponding to the maximum average value, and taking the intersection point as the target point.

In a possible embodiment, the second determining unit 1103 determines the adjustment amount of the service duration of the driver at the current time according to the target demand ratio and the passenger order amount at the current time, including:

acquiring a second historical demand ratio in the target area in the target time period;

performing difference calculation on the target required supply ratio and the second historical required supply ratio to obtain a required supply ratio difference;

And determining the adjustment quantity according to the ratio of the passenger bill quantity at the current time to the required supply ratio difference value.

In a possible embodiment, when the demand ratio difference is a positive value, increasing the service duration of the driver in the target area at the current time according to the adjustment amount;

And when the required supply ratio difference value is a negative value, reducing the service duration of the driver in the target area at the current time according to the adjustment quantity.

In a possible implementation manner, fig. 12 is a schematic structural diagram of another data processing apparatus according to a second embodiment of the present application, as shown in fig. 12, where the apparatus further includes:

And a transmitting unit 1104 for transmitting capacity adjustment information including a time period in which the service duration needs to be increased to a target driver including a driver who provides a service fixed in a time period in which the service duration needs to be reduced, after obtaining the adjustment amounts corresponding to the respective time periods.

The explanation of the second embodiment can refer to the explanation of the first embodiment, and will not be described in detail herein.

Example III

Fig. 13 is a schematic structural diagram of an electronic device according to a third embodiment of the present application, including: the system comprises a processor 1301, a storage medium 1302 and a bus 1303, wherein the storage medium 1302 stores machine readable instructions executable by the processor 1301, when the electronic device executes the data processing method described above, the processor 1301 communicates with the storage medium 1302 through the bus 1303, and the processor 1301 executes the machine readable instructions to perform the method described in the first embodiment.

Example IV

The fourth embodiment of the present application further provides a computer readable storage medium, where a computer program is stored, where the computer program is executed by a processor to perform the method according to the first embodiment.

Example five

Embodiments of the present application provide a computer program product comprising computer programs/instructions which, when executed by a processor, implement the steps of a data processing method.

It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described system and apparatus may refer to corresponding procedures in the method embodiments, and are not repeated in the present disclosure. In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners.

The above-described apparatus embodiments are merely illustrative, and the division of the modules is merely a logical function division, and there may be additional divisions when actually implemented, and for example, multiple modules or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, indirect coupling or communication connection of devices or modules, electrical, mechanical, or other form.

The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer readable storage medium executable by a processor. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk, etc.

The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily appreciate variations or alternatives within the scope of the present application. Therefore, the protection scope of the application is subject to the protection scope of the claims.

Claims

1. A method of data processing, comprising:

In response to determining that the first historical resource acquisition efficiency varies with the first historical demand-to-supply ratio for a plurality of days, and the variation of the first historical resource acquisition efficiency is less than a preset threshold, determining a target demand-to-supply ratio according to the first historical demand-to-supply ratio and the first historical resource acquisition efficiency for a plurality of days, including:

determining a target point with the distribution trend of the scattered points changed according to the coordinates of the scattered points, and taking the required supply ratio corresponding to the target point as the target required supply ratio;

2. The method of claim 1, wherein determining the target point at which the distribution trend of the scatter changes based on the coordinates of the scatter comprises:

3. The method of claim 2, wherein determining the target set with the greatest change in the distribution trend of the scattered points according to the coordinates of the scattered points corresponding to each candidate set comprises:

4. The method of claim 3, wherein the determining the target point based on coordinates of the scatter points corresponding to the set of targets comprises:

5. The method of claim 4, wherein determining the distribution difference value of the first set of points corresponding to the division point and the second set of points corresponding to the division point according to the coordinates of the first set of points corresponding to the division point and the coordinates of the second set of points corresponding to the division point comprises:

6. The method of claim 5, wherein the determining the target point from coordinates of a dividing point corresponding to the maximum distribution difference value and a scatter point corresponding to the target set comprises:

7. The method of claim 1, wherein the determining an adjustment of the service duration of the driver at the current time based on the target demand ratio and the passenger order amount at the current time comprises:

8. The method of claim 7, wherein the method further comprises:

When the required supply ratio difference is a positive value, increasing the service duration of the driver in the target area at the current time according to the adjustment quantity;

9. The method of claim 8, wherein the method further comprises:

After the adjustment amounts corresponding to the respective time periods are obtained, the capacity adjustment information including the time period for which the service duration needs to be increased is transmitted to the target driver including the driver who provides the service fixed in the time period for which the service duration needs to be reduced.

10. A data processing apparatus, comprising:

A first determining unit, configured to determine, in response to determining that the first historical resource acquisition efficiency varies with the first historical demand-to-supply ratio for a plurality of days, and an amount of variation of the first historical resource acquisition efficiency is smaller than a preset threshold, a target demand-to-supply ratio according to the first historical demand-to-supply ratio and the first historical resource acquisition efficiency for a plurality of days, including:

11. The apparatus of claim 10, wherein the first determining unit is configured to determine, based on coordinates of the scattered points, target points where a distribution trend of the scattered points changes, including:

12. The apparatus of claim 11, wherein the first determining unit is configured to determine, according to coordinates of the scattered points corresponding to each candidate set, a target set with a largest change in a distribution trend of the scattered points, the target set comprising:

13. The apparatus of claim 12, wherein the first determining unit determines the target point according to coordinates of a scatter point corresponding to the target set, comprising:

14. The apparatus of claim 13, wherein the first determining unit determines a distribution difference value of the first set of scattering points corresponding to the division point and the second set of scattering points corresponding to the division point based on coordinates of the first set of scattering points corresponding to the division point and coordinates of the second set of scattering points corresponding to the division point, comprising:

15. The apparatus of claim 14, wherein the first determining unit is configured to determine the target point according to coordinates of a dividing point corresponding to the maximum distribution difference value and a scatter point corresponding to the target set, and comprises:

16. The apparatus of claim 10, wherein the second determining unit, when determining the adjustment amount of the service duration of the driver at the current time based on the target demand ratio and the passenger order amount at the current time, includes:

17. The apparatus according to claim 16, wherein when the demand ratio difference is a positive value, a service duration of the driver in the target area at the current time is increased in accordance with the adjustment amount;

18. The apparatus of claim 17, wherein the apparatus further comprises:

and the sending unit is used for sending the capacity adjustment information containing the time period required to be increased in service duration to a target driver after obtaining the adjustment amount corresponding to each time period, wherein the target driver comprises a driver which is fixed in the time period required to be reduced in service duration and provides service.

19. An electronic device, comprising: a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating over the bus when the electronic device is running, the processor executing the machine-readable instructions to perform the steps of the method of any one of claims 1 to 9.

20. A computer-readable storage medium, characterized in that it has stored thereon a computer program which, when executed by a processor, performs the steps of the method according to any of claims 1 to 9.

21. A computer program product comprising computer programs/instructions which, when executed by a processor, implement the steps of the method of any one of claims 1 to 9.