基于用户消费行为的电力数据客户立体画像构建

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。

Construction of Power Data Customer Stereoscopic Portrait Based on User Consumption Behavior

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.