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A risk discovery method for user electricity bill settlement based on regional geographic location information

A technology of geographic location information and geographic location, applied in the power management field of power grid users, it can solve the problems of failure in the discovery process, no right to collect, and difficulty in building a decision-making model, so as to achieve the effect of accurate discovery and easy collection.

Active Publication Date: 2022-03-29
STATE GRID JILIN ELECTRIC POWER COMPANY LIMITED +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This type of method can be successful in some fields and experimental environments, but a key assumption of this type of method is to have a large amount of basic information data of users. Without these data, it is difficult to build a decision-making model.
For grid users, because grid companies are not government agencies or banks, many data (such as household income, age, housing, marriage) are difficult to obtain, and they have no right to collect them. The missing data will directly lead to the use of traditional methods. The discovery process for the risk of default failed

Method used

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  • A risk discovery method for user electricity bill settlement based on regional geographic location information
  • A risk discovery method for user electricity bill settlement based on regional geographic location information
  • A risk discovery method for user electricity bill settlement based on regional geographic location information

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0097] According to the present invention, a method for discovering the risk of user electricity bill settlement based on regional geographic location information includes the following steps:

[0098] S1, input the grid user arrears list History including the geographic location, input the initial calculation range LDis and the maximum calculation range HDis; obtain the number of users QNum in the History, and establish the user settlement area table QTable;

[0099] S101, input the grid user arrears list History including the geographic location, each item in the list is a structure, and the structure contains the following fields:

[0100] HID: User ID;

[0101] HX: the longitude coordinate of the user's geographic location;

[0102] HY: latitude coordinates of the user's geographic location;

[0103] HQF: whether the user is in arrears, 0 means no arrears, 1 means arrears;

[0104] S102, input the initial calculation range LDis, LDis is an integer and its default value ...

Embodiment 2

[0185] Take the electricity bill settlement of power grid users of a XXXX company as an example:

[0186] S1, input the grid user arrears list History including geographical location, the content of the table is as follows:

[0187] HID HX HY HQF 71001 126.351 43.882 1 81022 126.317 43.882 0 44020 126.376 43.871 0 35221 126.354 43.862 1 45214 126.343 43.833 1 　… 　

[0188] Enter the initial calculation range LDis=10 and the maximum calculation range HDis=200;

[0189] Get the number of users in History QNum=5021,

[0190] Create the user debt settlement area table QTable, the contents of which are as follows:

[0191] QID wxya QHY Qdis QUR QUR QCundu 71001 126.351 43.882 10 0 0 0 81022 126.317 43.882 10 0 0 0 44020 126.376 43.871 10 0 0 0 35221 126.354 43.862 10 0 0 0 45214 126.343 43.833 10 0 0 0 　… 　

[0192] S2. Establi...

Embodiment 3

[0201] In order to test and compare the effectiveness of the method, 2000 power grid users in a certain area are introduced as test data. The patent of the invention is compared with the traditional decision tree and neural network methods. The patent of the invention introduces the arrears and location data of power grid users; decision-making The tree and neural network methods introduce all possible open and collected data in the power grid user management system as attribute information for data analysis. The comparison results are as follows:

[0202] method Predict the number of users at risk The number of users who failed to judge the risk but had payment in arrears The method of the patent of the invention 　201 　13 decision tree 　1302 　240 neural network 　2520 　179

[0203] It can be seen that the number of users with risks predicted by the patent of the present invention is small, but the number of missed judgments is also small,...

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Abstract

The invention discloses a user electricity bill settlement risk discovery method based on regional geographical location information, using a consistency expansion operator to organize and store users with similar debt settlement conditions within a certain geographical area in a user debt settlement area table . Furthermore, for a new user, the debt settlement risk is calculated based on the distance between it and the items in the household debt settlement area table, so as to realize the discovery of the user's electricity bill settlement risk. By using the patent of the present invention, it is possible to achieve the goal of introducing fewer geographical location attributes that are easy to collect and more accurately discovering the risk of electricity bill arrears under the condition of only inputting a group of user locations and arrears information.

Description

Technical field: [0001] The invention discloses a method for discovering the risk of user electricity bill settlement based on regional geographical location information, relates to a method for discovering the risk of user electricity bill settlement risk, and belongs to the technical field of electricity consumption management of power grid users. Background technique: [0002] With the economic development and the expansion of power grid users, there will be a risk of some users' electricity bills being in arrears. If more users are in arrears, it will have a greater impact on the income of power grid companies. Therefore, it is very necessary to predict and make decisions on the risks of user electricity bill arrears, and preventive treatment of possible arrears in advance. Therefore, it is very important for the healthy and orderly operation of power grid companies to discover the risks of user electricity bill arrears. [0003] In the traditional field based on big dat...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/06G06Q50/06G06F16/29G06F16/25
CPCG06Q10/0635G06Q50/06G06F16/29G06F16/252
Inventor 王德春迟昊曹华彬陈雪莹孔祥靖王秀燕蔡雪梅马钲杨柏欢关平于淼于景阳裴洋毕莹赵宇菲
Owner STATE GRID JILIN ELECTRIC POWER COMPANY LIMITED
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