基于用户消费行为的电力数据客户立体画像构建
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引用本文:王小强,周珂宇.基于用户消费行为的电力数据客户立体画像构建[J].计算技术与自动化,2022,(4):166-172
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作者单位
王小强,周珂宇 (国网重庆铜梁供电公司重庆 402560) 
中文摘要:针对现有技术中用户消费行为数据繁多,电力数据分析能力较差的问题,构建了电力数据客户立体画像系统,实现了对用户消费行为的多信息分析。设计了FCM分类算法模型,实现对电力用户消费行为数据信息立体画像原始数据信息分类, 提高了数据分类能力。构建了灰色GM(1,1)模型,实现对用电行为数据信息的分析,从而提高电力数据客户立体画像分析和应用能力。试验表明,研究所提方法分类准确率达95%以上,误差在1%以下,准确度高,研究所提方法方法提高了电力用户消费行为数据信息分析能力。
中文关键词:用户消费行为  电力数据分析  立体画像  数据分类  数据信息
 
Construction of Power Data Customer Stereoscopic Portrait Based on User Consumption Behavior
Abstract:Aiming at the problems of a large amount of user consumption behavior data in the prior art and poor power data analysis capabilities, a three-dimensional portrait system of power data customers has been constructed to realize multi-information analysis of user consumption behavior. The FCM classification algorithm model is designed to realize the classification of the original data information of the three-dimensional portrait of the power user's consumption behavior data information and improve the data classification ability. A gray model was constructed to realize the analysis of electricity consumption data information, and as a result, promote the analysis and application capabilities of the three-dimensional portrait of electricity data customers. Experiments show that the classification accuracy rate of the method proposed by the research is more than 95%, the error is less than 1%, and the accuracy is high. This research method improves the ability of power user consumption behavior data information analysis.
keywords:consumer behavior  power data analysis  three-dimensional portrait  data classification  data information
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