摘要
Abstract
With the rapid development of the current economy and technology,the electricity consumption behavior of power users has shown an unprecedented diversification trend,and demand models have become increasingly diverse and changing rapidly.In order to effectively respond to this market change,power companies urgently need transformation and upgrading and adopt innovative marketing strategies to accurately match user needs,improve service quality and enhance market competitiveness.Aiming at many problems existing in traditional power marketing methods,such as rigid strategies,low matching of user needs,uneven distribution of power resources and serious waste of resources,this paper builds and proposes a personalized recommendation algorithm for power marketing based on big data analysis and artificial intelligence(AI)technology.The algorithm integrates advanced machine learning(ML)models and achieves accurate predictions of users'electricity consumption habits,preferences and future needs through in-depth mining of massive user electricity consumption data.Experimental results show that the personalized recommendation algorithm proposed in this paper performs well in improving user satisfaction and enhancing user stickiness,and significantly reduces operating costs and resource waste of power companies,providing strong support for the sustainable development of the power industry.关键词
电力营销/个性化推荐算法/大数据/人工智能/设计与应用Key words
power marketing/personalized recommendation algorithm/big data/artificial intelligence(AI)/design and application分类
信息技术与安全科学
