企业电力征信大数据价值挖掘与应用

doi:10.11959/j.issn.2096-0271.2021067

Abstract

Abstract:

Aiming at the shortcomings of traditional power credit investigation platform such as insufficient stability and low test accuracy, a big data power credit investigation platform was designed.The online analytical method was used to analyze power big data, which was divided into four categories: user behavior, expense rules, user value and personal credit.Based on the modular structure, the data acquisition module, data analysis module and user interaction module were optimized respectively.The KNN and cross validation method were used to classify and process the power consumption data, and the regional power consumption law was obtained, so as to design and adjust the distribution scheme.Finally, the platform was compared with the traditional power credit investigation platform.The experimental results show that the stability and accuracy of the platform are improved, and the accuracy is as high as 98.9% during the test.

Key words: big data model, power credit investigation, comprehensive algorithm, network architecture, system testing

CLC Number:

U495

Baojiang XIN, Dewen LI, Lanlan WANG. Value mining and application of big data in enterprise power credit investigation[J]. Big Data Research, 2021, 7(6): 138-146.

Figures/Tables 10

References 24

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对比项	用电量预测值/万kW·h	用电量真实值/万kW·h	缴费预测值/万元	缴费真实值/万元	准确性
一号平台	7.0	5.2	4.2	3.51	74.2%
二号平台	5.6	5.2	4.0	3.51	85.3%
本文平台	5.0	5.2	3.49	3.51	98.9%

Value mining and application of big data in enterprise power credit investigation

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