Design and Implementation of Electric Charge Arrears Prediction System

摘要：

　　Electric charge is the primary income for the power company.However, collecting electric charge is much difficult due to the existence of the risky consumer which makes the huge impact on the normal operation and development of the company.So the arrear problem of the risky customers has become one of the focus problems.Based on the gettable electric data from some areas, this paper proposed an integral system which can predict risky customers according to the various scenarios.In the system, the Random Forest (RF) model and Extreme Learning Machine (ELM) model are integrated that can effectively analyze the obvious features of the risky customers and predict the potential risky customers.In the experiment part,it has shown that our system applied to arrear risky customersprediction has higher performance.

关键词： risky customers Random Forest Extreme Learning Machine

作者: Wenzhong Guo Wei Hong Wanhua Li Kun Guo

作者单位: College of Mathematics and Computer Sciences Fuzhou University Fuzhou 350108, China

会议类型: 国际会议

会议名称: The 12th Web Information System and Application Conference第十二届全国Web信息系统及其应用学术会议(WISA2015)、全国第十次语义Web 与本体论学术研讨会(SWON2015)、全国第九次电子政务技术及应用学术研讨会(EGTA2015)

会议地点: 济南

会议语种:英文

页码: 309-313

在线出版日期: 2015-09-11（万方平台首次上网日期，不代表论文的发表时间）