WO2019061992A1

WO2019061992A1 - Method for optimizing investigation grid, electronic device, and computer readable storage medium

Info

Publication number: WO2019061992A1
Application number: PCT/CN2018/076179
Authority: WO
Inventors: 邓坤; 王建明; 肖京
Original assignee: 平安科技（深圳）有限公司
Priority date: 2017-09-30
Filing date: 2018-02-10
Publication date: 2019-04-04
Also published as: CN107844851A; CN107844851B

Abstract

The present invention discloses a method for optimizing an investigation grid, comprising the following steps: extracting car insurance claim information pre-stored in a database; performing cluster analysis of the extracted car insurance claim information to obtain a car insurance case hotspot area and time period; and adjusting, according to the car insurance case hotspot area and time period obtained after the cluster analysis has been performed, an investigation area grid preset in the database. The present invention can optimize an existing investigation grid, thereby improving overall investigation efficiency.

Description

Survey grid optimization method, electronic device and computer readable storage medium

This application claims the priority of the Chinese Patent Application filed on Sep. 30, 2017, the Chinese Patent Office, Application No. 201710916177.X, entitled "Inspection Grid Optimization Method, Electronic Device, and Computer Readable Storage Medium", All content is incorporated by reference in the application.

Technical field

The present application relates to the field of computer information technology, and in particular, to a survey grid optimization method, an electronic device, and a computer readable storage medium.

Background technique

At present, when the auto insurance industry divides the auto insurance survey grid, the traditional urban administrative area division method is generally adopted. This grid division method cannot effectively optimize the grid and dynamically adjust. Therefore, the prior art method for dividing the vehicle inventory network is not reasonable enough and needs to be improved.

Summary of the invention

In view of this, the present application proposes a survey grid optimization method, an electronic device and a computer readable storage medium. By clustering the key information of the extracted vehicle insurance report, the existing survey grid can be optimized to improve the overall survey work efficiency. .

First, in order to achieve the above object, the present application provides an electronic device including a memory and a processor, where the memory stores a search grid optimization system operable on the processor, the survey network The grid optimization system is implemented by the processor to implement the following steps:

Extracting pre-stored car insurance report information in the database;

Performing cluster analysis on the extracted vehicle insurance report information to obtain a hotspot area and a hot spot time period of the automobile insurance case;

According to the case hotspot area and the hot spot time period obtained by the cluster analysis, the grid of the survey area set in advance in the database is adjusted.

Preferably, the obtaining of the hotspot area and the hotspot period of the auto insurance case comprises:

Extracting location information and time information of a car insurance case within a preset time period;

Set different thresholds required for cluster analysis of hotspots, cluster analysis of hotspots according to location information of auto insurance cases, and calculate hotspots of auto insurance cases under different thresholds;

According to the predetermined condition, the hotspot area of the auto insurance case under different thresholds is analyzed, and the optimal threshold and the best hotspot area meeting the predetermined condition are obtained;

According to the time information of the car insurance case in the best hot spot area, cluster analysis of the hot spot time segment is performed to obtain the hot spot time period of the car insurance case.

Preferably, if the number of vehicle insurance reports in a certain area within a preset time period is greater than or equal to a preset threshold, determining that the area is a hotspot area;

The different thresholds required for the cluster analysis of the hotspot area include a first preset threshold, a second preset threshold, and a third preset threshold. The hotspot area for calculating a car insurance case under different thresholds includes:

Counting all the hotspot areas in which the number of vehicle insurance reports is greater than or equal to the first preset threshold in the preset time period, and obtaining the first group of hotspot areas, and counting all the hotspot areas in the preset time period that the number of vehicle insurance reports is greater than or equal to the second preset threshold. And obtaining a second group of hotspot areas, and collecting all the hotspot areas in which the number of vehicle insurance reports is greater than or equal to the third preset threshold in the preset time period, to obtain the third group of hotspot areas.

Preferably, the optimal hotspot area is the most hotspot area group that meets the predetermined condition, and the optimal threshold is a preset threshold corresponding to the optimal hotspot area.

Preferably, the predetermined condition is a workload of the surveying personnel;

The pre-set survey area grid in the adjustment database includes: adding survey personnel of the hot spot area and the hot spot time period, reducing survey personnel of non-hot spot areas and non-hot spot time periods, or merging non-hot spot areas.

In addition, in order to achieve the above object, the present application further provides a method for optimizing a survey grid, which is applied to an electronic device, and the method includes:

Extracting pre-stored car insurance report information in the database;

The pre-set survey area grid in the database is adjusted according to the case hotspot area and the hot spot time period obtained by the cluster analysis.

Preferably, the optimal hotspot area is the hotspot area group with the largest number of the predetermined hot conditions, and the optimal threshold is a preset threshold corresponding to the best hotspot area;

The predetermined condition is a workload of the surveying personnel; and

The grid of the survey area preset in the adjustment database includes: a survey person who increases the hotspot area and the hot spot time period of the case, and reduces the non-hot spot area and the non-hot spot time section of the survey personnel or merges the non-hot spot area.

Further, in order to achieve the above object, the present application further provides a computer readable storage medium storing a survey grid optimization system, the survey grid optimization system being executable by at least one processor, The step of causing the at least one processor to perform the survey grid optimization method as described above.

Compared with the prior art, the electronic device, the survey grid optimization method and the computer readable storage medium proposed by the present application perform cluster analysis on key information of the extracted vehicle insurance report (such as report city, region, and time distribution). Obtain the hotspot area of the auto insurance case and the hotspot time period, and adjust the grid of the existing survey area according to the results of the cluster analysis. This application can optimize the existing survey grid and improve the overall survey work efficiency, and can be based on the latest network. The grid data is dynamically updated.

DRAWINGS

1 is a schematic diagram of an optional hardware architecture of an electronic device of the present application;

2 is a schematic diagram of a program module of an embodiment of a survey grid optimization system in an electronic device of the present application;

FIG. 3 is a schematic diagram of an implementation process of an embodiment of a method for optimizing a survey grid according to the present application.

Reference mark:

电子设备 Electronic equipment	22
存储器Memory	21twenty one
处理器processor	22twenty two
网络接口Network Interface	23twenty three
查勘网格优化系统Survey grid optimization system	2020
抽取模块 Extraction module	201201
获取模块 Acquisition module	202202

优化模块 Optimization module	203203
流程步骤Process step	S31-S33S31-S33

The implementation, functional features and advantages of the present application will be further described with reference to the accompanying drawings.

Detailed ways

In order to make the objects, technical solutions, and advantages of the present application more comprehensible, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It is understood that the specific embodiments described herein are merely illustrative of the application and are not intended to be limiting. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present application without departing from the inventive scope are the scope of the present application.

It should be noted that the descriptions of "first", "second" and the like in the present application are for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. . Thus, features defining "first" and "second" may include at least one of the features, either explicitly or implicitly. In addition, the technical solutions between the various embodiments may be combined with each other, but must be based on the realization of those skilled in the art, and when the combination of the technical solutions is contradictory or impossible to implement, it should be considered that the combination of the technical solutions does not exist. Nor is it within the scope of protection required by this application.

It is further to be understood that the term "comprises", "comprises" or any other variations thereof is intended to encompass a non-exclusive inclusion, such that a process, method, article, or device that comprises a And includes other elements not explicitly listed, or elements that are inherent to such a process, method, article, or device. An element that is defined by the phrase "comprising a ..." does not exclude the presence of additional equivalent elements in the process, method, item, or device that comprises the element.

First of all, the present application proposes an electronic device 2.

Referring to FIG. 1, it is a schematic diagram of an optional hardware architecture of the electronic device 2 of the present application. In this embodiment, the electronic device 2 may include, but is not limited to, a memory 21, a processor 22, and a network interface 23 that can communicate with each other through a system bus. It is pointed out that FIG. 1 only shows the electronic device 2 with the components 21-23, but it should be understood that not all illustrated components are required to be implemented, and more or fewer components may be implemented instead.

The electronic device 2 may be a computing device such as a rack server, a blade server, a tower server, or a rack server. The electronic device 2 may be an independent server or a server cluster composed of multiple servers. .

The memory 21 includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (eg, SD or DX memory, etc.), a random access memory (RAM), a static Random access memory (SRAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), programmable read only memory (PROM), magnetic memory, magnetic disk, optical disk, and the like. In some embodiments, the memory 21 may be an internal storage unit of the electronic device 2, such as a hard disk or memory of the electronic device 2. In other embodiments, the memory 21 may also be an external storage device of the electronic device 2, such as a plug-in hard disk equipped on the electronic device 2, a smart memory card (SMC), and a secure digital device. (Secure Digital, SD) card, flash card, etc. Of course, the memory 21 may also include both an internal storage unit of the electronic device 2 and an external storage device thereof. In this embodiment, the memory 21 is generally used to store an operating system and various application software installed in the electronic device 2, such as program codes of the survey grid optimization system 20. Further, the memory 21 can also be used to temporarily store various types of data that have been output or are to be output.

The processor 22 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments. The processor 22 is typically used to control the overall operation of the electronic device 2, such as performing control and processing related to data interaction or communication with the electronic device 2. In this embodiment, the processor 22 is configured to run program code or process data stored in the memory 21, such as running the survey grid optimization system 20 and the like.

The network interface 23 may comprise a wireless network interface or a wired network interface, which is typically used to establish a communication connection between the electronic device 2 and other electronic devices. For example, the network interface 23 is configured to connect the electronic device 2 to an external data platform through a network, and establish a data transmission channel and a communication connection between the electronic device 2 and an external data platform. The network may be an intranet, an Internet, a Global System of Mobile communication (GSM), a Wideband Code Division Multiple Access (WCDMA), a 4G network, or a 5G network. Wireless or wired networks such as network, Bluetooth, Wi-Fi, etc.

So far, the application environment of the various embodiments of the present application and the hardware structure and functions of related devices have been described in detail. Hereinafter, various embodiments of the present application will be proposed based on the above-described application environment and related devices.

Referring to FIG. 2, it is a program module diagram of an embodiment of the survey grid optimization system 20 in the electronic device 2 of the present application. In this embodiment, the survey grid optimization system 20 may be divided into one or more program modules, the one or more program modules being stored in the memory 21 and being processed by one or more processors. (Processing in the present embodiment for the processor 22) to complete the application. For example, in FIG. 2, the survey grid optimization system 20 can be divided into an extraction module 201, an acquisition module 202, and an optimization module 203. A program module as referred to in the present application refers to a series of computer program instruction segments capable of performing a specific function, which is more suitable than the program to describe the execution process of the survey grid optimization system 20 in the electronic device 2. The function of each program module 201-203 will be described in detail below.

The extraction module 201 is configured to extract pre-stored vehicle insurance report information in a database (such as the memory 21 of the electronic device 2). Preferably, in this embodiment, the vehicle insurance report information includes, but is not limited to, information on the city, region, and time distribution (such as different time periods, working days, non-working days, holidays, etc.) of the automobile insurance report.

The obtaining module 202 is configured to perform cluster analysis on the extracted vehicle insurance report information, and obtain a hotspot area (such as a city center area) and a hotspot time period (such as 7:00-9:00 on the working day). 5:30-7:30 pm). Preferably, in this embodiment, the DBSCAN clustering algorithm may be used to perform cluster analysis on the extracted vehicle insurance report information.

Preferably, in this embodiment, the obtaining of the hotspot area and the hotspot period of the auto insurance case comprises the following steps:

(1) Extract the location information (such as latitude and longitude coordinate information) and time information of the auto insurance case within the preset time period (such as within the past 24 hours).

(2) Set different thresholds required for cluster analysis of hotspots, cluster analysis of hotspots according to the location information of auto insurance cases, and calculate hotspots of auto insurance cases under different thresholds. Wherein, if the number of vehicle insurance reports in a certain period of time is greater than or equal to a preset threshold (eg, 5 times), the area is determined to be a hotspot area.

Preferably, in this embodiment, different thresholds required for cluster analysis of the hotspot region include, but are not limited to, a first preset threshold (eg, 3 times), a second preset threshold (eg, 5 times), Three preset thresholds (such as 7 times). Correspondingly, all hotspots whose number of car insurance reports is greater than or equal to the first preset threshold are counted in the preset time period, and the first group of hotspots (such as 10) are obtained; the number of car insurance reports in the preset time period is greater than or equal to The second hotspot area is obtained by using the second hotspot area (for example, 15); and the hotspot report period is greater than or equal to the third preset threshold in the preset preset period, and the third hotspot area is obtained. Such as 20).

(3) Analyze the hotspot area of the auto insurance case under different thresholds according to the predetermined conditions, and obtain the optimal threshold and the best hotspot area that meet the predetermined conditions. The optimal hotspot area is the hotspot area group (such as the second set of hotspot areas) that meets the predetermined condition. The optimal threshold is a preset threshold corresponding to the best hotspot area. For example, if the best hotspot area is the second set of hotspot areas, the optimal threshold is a second preset threshold corresponding to the second set of hotspot areas.

Preferably, in the embodiment, the predetermined condition may be a workload of the surveying personnel. For example, if the workload of an existing surveyor can only support up to 18 hotspots, the best hotspot area is determined to be the second hotspot area (the number is 15), and the optimal threshold is the second preset threshold (5 times). ).

(4) According to the time information of the car hazard case in the best hot spot area, cluster analysis of the hot spot time period to obtain the hot spot time period of the car insurance case (such as 7:00-9:00 on the working day, 5:00 in the evening) 30-7:30). In this embodiment, the DBSCAN clustering algorithm may also be used to perform hotspot time segment clustering analysis, and details are not described herein again.

The optimization module 203 is configured to adjust a pre-set survey area grid in the database according to the case hotspot area and the hotspot time period acquired by the cluster analysis.

Preferably, in this embodiment, the preset survey area grid in the adjustment database includes: a survey person who increases the hotspot area and the hot spot time period of the case, and reduces the survey personnel of the non-hot spot area and the non-hot spot time period. Or merge non-hot spots.

Further, in other embodiments, the optimization module 203 is further configured to:

Every predetermined time interval (such as 1 day), update grid data (such as map data in the grid area) and case data (such as the latest accident point report data) to achieve dynamic adjustment and optimization of the survey area grid.

Through the above-mentioned program modules 201-203, the survey grid optimization system 20 proposed by the present application clusters the key information of the extracted vehicle insurance reports (such as the report city, region, and time distribution), and obtains hotspot areas and hotspots of the automobile insurance cases. The time period and the division of the grid of the existing survey area are adjusted according to the results of the cluster analysis. This application can optimize the existing survey grid, improve the overall survey work efficiency, and can dynamically update according to the latest grid data.

In addition, the present application also proposes a survey grid optimization method.

Referring to FIG. 3, it is a schematic flowchart of an implementation process of an embodiment of the search grid optimization method of the present application. In this embodiment, the order of execution of the steps in the flowchart shown in FIG. 3 may be changed according to different requirements, and some steps may be omitted.

In step S31, the vehicle insurance report information pre-stored in the database (such as the memory 21 of the electronic device 2) is extracted. Preferably, in this embodiment, the vehicle insurance report information includes, but is not limited to, information on the city, region, and time distribution (such as different time periods, working days, non-working days, holidays, etc.) of the automobile insurance report.

Step S32, performing cluster analysis on the extracted vehicle insurance report information, obtaining a hot spot area of the auto insurance case (such as a city center area) and a hotspot time period (eg, 7:00-9:00 on the working day, 5:30 pm) 7:30). Preferably, in this embodiment, the DBSCAN clustering algorithm may be used to perform cluster analysis on the extracted vehicle insurance report information.

Step S33: Adjust the pre-set survey area grid in the database according to the case hotspot area and the hotspot time period obtained by the cluster analysis.

Further, in other embodiments, the survey grid optimization method further includes the following steps:

Through the above steps S31-S33, the survey grid optimization method proposed by the present application clusters the key information of the extracted vehicle insurance report (such as the report city, region, and time distribution), and obtains the hotspot area and the hot spot time period of the auto insurance case. And according to the results of the cluster analysis, the division of the grid of the existing survey area is adjusted. This application can optimize the existing survey grid, improve the overall survey work efficiency, and can dynamically update according to the latest grid data.

Further, in order to achieve the above object, the present application further provides a computer readable storage medium (such as a ROM/RAM, a magnetic disk, an optical disk), where the computer readable storage medium stores a survey grid optimization system 20, the survey The grid optimization system 20 can be executed by at least one processor 22 to cause the at least one processor 22 to perform the steps of the survey grid optimization method as described above.

Through the description of the above embodiments, those skilled in the art can clearly understand that the foregoing embodiment method can be implemented by means of software plus a necessary general hardware platform, and can also be implemented by hardware, but in many cases, the former is A better implementation. Based on such understanding, the technical solution of the present application, which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a storage medium (such as ROM/RAM, disk, The optical disc includes a number of instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the methods described in various embodiments of the present application.

The preferred embodiments of the present application have been described above with reference to the drawings, and are not intended to limit the scope of the application. The serial numbers of the embodiments of the present application are merely for the description, and do not represent the advantages and disadvantages of the embodiments. Additionally, although logical sequences are shown in the flowcharts, in some cases the steps shown or described may be performed in a different order than the ones described herein.

A person skilled in the art can implement the present application in various variants without departing from the scope and spirit of the present application. For example, the features of one embodiment can be used in another embodiment to obtain another embodiment. The equivalent structure or equivalent process transformations made by the present specification and the contents of the drawings, or directly or indirectly applied to other related technical fields, are all included in the scope of patent protection of the present application.

Claims

An electronic device, comprising: a memory and a processor, wherein the memory stores a survey grid optimization system operable on the processor, the survey grid optimization system being The processor implements the following steps when it executes:

Extracting pre-stored car insurance report information in the database;

Performing cluster analysis on the extracted vehicle insurance report information to obtain a hotspot area and a hot spot time period of the automobile insurance case;

The pre-set survey area grid in the database is adjusted according to the case hotspot area and the hot spot time period obtained by the cluster analysis.
The electronic device according to claim 1, wherein the obtaining of the hotspot area and the hotspot period of the auto insurance case comprises:

Extracting location information and time information of a car insurance case within a preset time period;

Set different thresholds required for cluster analysis of hotspots, cluster analysis of hotspots according to location information of auto insurance cases, and calculate hotspots of auto insurance cases under different thresholds;

According to the predetermined condition, the hotspot area of the auto insurance case under different thresholds is analyzed, and the optimal threshold and the best hotspot area meeting the predetermined condition are obtained;

According to the time information of the car insurance case in the best hot spot area, cluster analysis of the hot spot time segment is performed to obtain the hot spot time period of the car insurance case.
The electronic device according to claim 2, wherein if the number of vehicle insurance reports in an area in the predetermined time period is greater than or equal to a preset threshold, determining that the area is a hotspot area;

The different thresholds required for the cluster analysis of the hotspot area include a first preset threshold, a second preset threshold, and a third preset threshold. The hotspot area for calculating a car insurance case under different thresholds includes:

Counting all the hotspot areas in which the number of vehicle insurance reports is greater than or equal to the first preset threshold in the preset time period, and obtaining the first group of hotspot areas, and counting all the hotspot areas in the preset time period that the number of vehicle insurance reports is greater than or equal to the second preset threshold. And obtaining a second group of hotspot areas, and collecting all the hotspot areas in which the number of vehicle insurance reports is greater than or equal to the third preset threshold in the preset time period, to obtain the third group of hotspot areas.
The electronic device according to claim 2, wherein the optimal hotspot area is the hotspot area group having the largest number that meets the predetermined condition, and the optimal threshold is a preset threshold corresponding to the optimal hotspot area.
The electronic device according to claim 3, wherein the optimal hotspot area is the hotspot area group having the largest number that meets the predetermined condition, and the optimal threshold is a preset threshold corresponding to the optimal hotspot area.
The electronic device according to claim 4, wherein said predetermined condition is a workload of the surveying personnel;

The pre-set survey area grid in the adjustment database includes: adding survey personnel of the hot spot area and the hot spot time period, reducing survey personnel of non-hot spot areas and non-hot spot time periods, or merging non-hot spot areas.
The electronic device according to claim 5, wherein said predetermined condition is a workload of the surveying personnel;

The pre-set survey area grid in the adjustment database includes: adding survey personnel of the hot spot area and the hot spot time period, reducing survey personnel of non-hot spot areas and non-hot spot time periods, or merging non-hot spot areas.
A survey grid optimization method is applied to an electronic device, and the method includes:

Extracting pre-stored car insurance report information in the database;

Performing cluster analysis on the extracted vehicle insurance report information to obtain a hotspot area and a hot spot time period of the automobile insurance case;

The pre-set survey area grid in the database is adjusted according to the case hotspot area and the hot spot time period obtained by the cluster analysis.
The method for optimizing a survey grid according to claim 8, wherein the obtaining of the hotspot area and the hotspot period of the auto insurance case comprises:

Extracting location information and time information of a car insurance case within a preset time period;

Set different thresholds required for cluster analysis of hotspots, cluster analysis of hotspots according to location information of auto insurance cases, and calculate hotspots of auto insurance cases under different thresholds;

According to the predetermined condition, the hotspot area of the auto insurance case under different thresholds is analyzed, and the optimal threshold and the best hotspot area meeting the predetermined condition are obtained;

According to the time information of the car insurance case in the best hot spot area, cluster analysis of the hot spot time segment is performed to obtain the hot spot time period of the car insurance case.
The method for optimizing the survey grid according to claim 9, wherein if the number of vehicle insurance reports in a certain period of time is greater than or equal to a preset threshold, determining that the area is a hotspot area;

The different thresholds required for the cluster analysis of the hotspot area include a first preset threshold, a second preset threshold, and a third preset threshold. The hotspot area for calculating a car insurance case under different thresholds includes:

Counting all the hotspot areas in which the number of vehicle insurance reports is greater than or equal to the first preset threshold in the preset time period, and obtaining the first group of hotspot areas, and counting all the hotspot areas in the preset time period that the number of vehicle insurance reports is greater than or equal to the second preset threshold. And obtaining a second group of hotspot areas, and collecting all the hotspot areas in which the number of vehicle insurance reports is greater than or equal to the third preset threshold in the preset time period, to obtain the third group of hotspot areas.
The method for optimizing the survey grid according to claim 9, wherein the optimal hotspot area is the hotspot group with the largest number of the predetermined conditions, and the optimal threshold is the pre-corresponding to the best hotspot area. Set the threshold.
The method for optimizing the survey grid according to claim 10, wherein the optimal hotspot area is the hotspot group with the largest number of the predetermined conditions, and the optimal threshold is a pre-corresponding to the best hotspot area. Set the threshold.
The method for optimizing a survey grid according to claim 11, wherein the predetermined condition is a workload of the surveying personnel;

The pre-set survey area grid in the adjustment database includes: adding survey personnel of the hot spot area and the hot spot time period, reducing survey personnel of non-hot spot areas and non-hot spot time periods, or merging non-hot spot areas.
The method for optimizing a survey grid according to claim 12, wherein the predetermined condition is a workload of the surveying personnel;

The pre-set survey area grid in the adjustment database includes: adding survey personnel of the hot spot area and the hot spot time period, reducing survey personnel of non-hot spot areas and non-hot spot time periods, or merging non-hot spot areas.
A computer readable storage medium storing a survey grid optimization system, the survey grid optimization system being executable by at least one processor, the survey grid optimization system being The following steps are implemented during execution:

Extracting pre-stored car insurance report information in the database;

Performing cluster analysis on the extracted vehicle insurance report information to obtain a hotspot area and a hot spot time period of the automobile insurance case;

According to the case hotspot area and the hot spot time period obtained by the cluster analysis, the grid of the survey area set in advance in the database is adjusted.
The computer readable storage medium according to claim 15, wherein the obtaining of the hotspot area and the hotspot period of the auto insurance case comprises:

Extracting location information and time information of a car insurance case within a preset time period;

Set different thresholds required for cluster analysis of hotspots, cluster analysis of hotspots according to location information of auto insurance cases, and calculate hotspots of auto insurance cases under different thresholds;

According to the predetermined condition, the hotspot area of the auto insurance case under different thresholds is analyzed, and the optimal threshold and the best hotspot area meeting the predetermined condition are obtained;

According to the time information of the car insurance case in the best hot spot area, cluster analysis of the hot spot time segment is performed to obtain the hot spot time period of the car insurance case.
The computer readable storage medium according to claim 16, wherein if the number of vehicle insurance reports in a certain period of time is greater than or equal to a preset threshold, determining that the area is a hotspot area;

The different thresholds required for the cluster analysis of the hotspot area include a first preset threshold, a second preset threshold, and a third preset threshold. The hotspot area for calculating a car insurance case under different thresholds includes:

Counting all the hotspot areas in which the number of vehicle insurance reports is greater than or equal to the first preset threshold in the preset time period, and obtaining the first group of hotspot areas, and counting all the hotspot areas in the preset time period that the number of vehicle insurance reports is greater than or equal to the second preset threshold. And obtaining a second group of hotspot areas, and collecting all the hotspot areas in which the number of vehicle insurance reports is greater than or equal to the third preset threshold in the preset time period, to obtain the third group of hotspot areas.
The computer readable storage medium according to claim 16, wherein the optimal hot spot area is a hotspot area group having the largest number that meets the predetermined condition, and the optimal threshold value is a pre-corresponding to the optimal hot spot area. Set the threshold.
The computer readable storage medium according to claim 17, wherein the optimal hot spot area is a hotspot area group having the largest number that meets the predetermined condition, and the optimal threshold value is a pre-corresponding to the optimal hot spot area. Set the threshold.
The computer readable storage medium according to claim 18 or 19, wherein the predetermined condition is a workload of the surveying personnel;

The pre-set survey area grid in the adjustment database includes: adding survey personnel of the hot spot area and the hot spot time period, reducing survey personnel of non-hot spot areas and non-hot spot time periods, or merging non-hot spot areas.