Research on Customer Electricity Consumption Behavior Analysis Based on Big Data

A new big data algorithm has been proposed to address the problem of slow and inefficient electricity consumption behavior of existing technology analysis customers. This scheme adopts a hybrid big data algorithm to achieve multiple analyses of marketing big data customers' electricity consumption behavior. The improved K-means clustering algorithm is integrated into the Apriori algorithm model, and the Extreme Learning Machine (ELM) principle is used to quickly classify marketing big data customers' electricity consumption behavior, improving classification ability. Through data association mining, the potential relationship between user electricity consumption behavior and influencing factors is accurately discovered, which improves the ability of electricity analysis. The experiment showed that the accuracy of the research plan was as high as 93.4%.