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《Technology Intelligence Engineering》 2018-03
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Electricity Customer Value Evaluation Modeling Based on Semi-supervised Learning

LIU Gang;GAO Di;FU Weiwei;LIU Xia;LIU Xin;Operation Monitor Center,State Grid Jibei Electric Power Company;School of Computer and Communication Engineering, University of Science & Technology Beijing;Beijing Bowang Huake Technology Co.Ltd.;  
With the gradual opening up of Chinese electricity market, large-scale monopoly power enterprises are forced to join in the fierce competition. The evaluation of electricity users becomes more and more important. This paper proposes an evaluation model based on electric business behaviors using semi-supervised machine learning algorithms, and changes the evaluation problems to classification problems. By building predict models using random forest and semi-random forest algorithm, it can decrease the influence of class imbalance problems and give an accurate prediction of user business behaviors, which may provide a new method to evaluate the electricity user value.
【Fund】: 国家科技支撑计划项目(2017YFB1002304)
【CateGory Index】: F274;F426.61
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