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Electricity fee collection risk assessment device based on big data platform clustering algorithm and method thereof

A technology of big data platform and clustering algorithm, which is applied in the field of electricity fee recovery risk assessment device based on big data platform clustering algorithm, can solve the problems of charging difficulties of electric power enterprises, recovery risk assessment electricity fee cannot be fully recovered on time and economic pressure of enterprises, etc. , to achieve the effect of avoiding the risk of not paying fees on time and reducing the risk of not being able to return on time

Inactive Publication Date: 2015-10-21
STATE GRID CORP OF CHINA +1
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AI Technical Summary

Problems solved by technology

[0003] The present invention provides a device and method for risk assessment of electricity fee recovery based on clustering algorithm of big data platform, which overcomes the above-mentioned deficiencies in the prior art, and can effectively Solve the problem that the existing electricity customers are in arrears of electricity bills, which makes it difficult for electric power companies to charge fees, and more effectively solve the problem that due to the lack of recycling risk assessment work of power companies, the recyclable electricity charges cannot be recovered in full and on time, which has brought huge economic pressure to the company.

Method used

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  • Electricity fee collection risk assessment device based on big data platform clustering algorithm and method thereof
  • Electricity fee collection risk assessment device based on big data platform clustering algorithm and method thereof

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Embodiment 1

[0025] Embodiment one: as attached figure 1 , 2 As shown, a risk assessment device for electricity fee recovery based on the clustering algorithm of the big data platform, including an electricity consumption unit characteristic data import module 1, a cluster data mining module and an electricity consumption unit credit evaluation system output module 2; the electricity consumption unit characteristic data The import module 1 extracts the massive data of social attribute indicators, value attribute indicators and behavior attribute indicators of power consumers and stores them in the big data Hadoop platform. The clustering data mining module performs parallel data processing and performs multiple iterative analysis and calculation of the data. Compare the changes before and after the iterative analysis of the data, and judge the credit rating of the power consumer by comparing the difference between the data change and the given threshold. And output the credit rating o...

Embodiment 2

[0031] Embodiment two: if figure 1 , 2 As shown, a method of using a risk assessment device for electricity charge recovery based on a big data platform clustering algorithm includes the following steps:

[0032] Step 1: Obtain the credit parameter database of the electricity consumer, including social attribute index data, value attribute index data and behavior attribute index data, and then enter step 2;

[0033] Step 2: The credit parameters are used as the basic indicators for establishing the credit evaluation system of power consumers. The credit ratings are divided into six grades from high to low, namely AAA grade, AA grade, A grade, B grade, C grade, and D grade. Then go to step three;

[0034] Step 3: Import module of characteristic data of power consumption unit imports collected credit parameter database into cluster data mining module, distributed data processing unit of cluster data mining module performs distributed processing on data, and divides t...

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Abstract

The invention relates to the technical field of fee collection risk assessment, and provides an electricity fee collection risk assessment device based on a big data platform clustering algorithm and a method thereof. The device comprises an electricity consuming unit feature data import module, a clustering data mining module and an electricity consuming unit credit evaluation system output module. The electricity consuming unit feature data import module extracts a social attribute indicator, a value attribute indicator, a behavior attribute indicator and other mass data of an electricity consuming unit and stores the mass data in a big data platform. The clustering data mining module performs parallel iterative analysis processing one the data and preliminarily judges the credit rating to which the electricity consuming unit belongs. The electricity consuming unit credit evaluation system output module confirms and outputs the credit rating of the electricity consuming unit according to data division of the clustering data mining module. The risk that the electricity consuming unit does not pay electricity fee on time can be effectively avoided so that the risk that funds of electric power enterprises cannot be withdrawn on time can be effectively reduced further.

Description

technical field [0001] The invention relates to the technical field of charge recovery risk assessment, and relates to a risk assessment device and method for electricity charge recovery based on a big data platform clustering algorithm. Background technique [0002] With the continuous deepening of the reform of the power system, the declining electricity charge recovery rate has affected the development of power companies to a considerable extent. The huge arrears deficit has hindered the normal business activities of power companies and increased financial and operational risks. Therefore, How to strengthen management from within the enterprise and improve the recovery rate of electricity charges has become an urgent task for electric power enterprises. Electricity fee recovery is the last link in the whole production process of electric power enterprises, and it is also the final manifestation of the production and operation results of electric power enterprises. Timely...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/06
Inventor 尼加提·纳吉米周文婷安文燕马天福韩双立付长松周鹏刘信马斌王涛
Owner STATE GRID CORP OF CHINA
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