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Research on early warning of electric power customers' credit risk based on SVM
Wang ZF(王忠锋); Yu, Haifei; Hu, Bo; Zhang, Tao; Lv, Bo
作者部门工业控制网络与系统研究室
会议名称36th Chinese Control Conference, CCC 2017
会议日期July 26-28, 2017
会议地点Dalian, China
会议主办者Dalian University of Technology ; Systems Engineering Society of China (SESC) ; Technical Committee on Control Theory (TCCT), Chinese Association of Automation (CAA)
会议录名称Proceedings of the 36th Chinese Control Conference, CCC 2017
出版者IEEE Computer Society
出版地Piscataway, NJ, USA
2017
页码10209-10213
收录类别EI ; CPCI(ISTP)
EI收录号20174404320465
WOS记录号WOS:000432015504030
产权排序1
ISSN号1934-1768
ISBN号978-1-5386-2918-5
关键词Svm Credit Risk Early-warning Model Power Market
摘要

Aiming at the deception phenomena in the electric power market that disorder the power trading, the early warning problem of power users' credit risk in the power market was studied. To solve the problem, an early warning model based on SVM (Support Vector Machine) was purposed. First the evaluation criteria system and grading standard were discussed in detail. Secondly the early warning model based on SVM was built and the optimization of parameters was analyzed. Finally the data of Liaoning Electric Power Co., Ltd., from 2013 to 2016 is chosen as the sample data for verifying and simulating the early-warming model of power customers' credit risk. The results showed the effectiveness of the proposed method.

语种英语
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文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/21051
专题工业控制网络与系统研究室
通讯作者Wang ZF(王忠锋)
作者单位1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China
2.College of Business Administration, Northeastern University, Shenyang, 110169, China
3.State Grid Liaoning Electric Power Co. Ltd., Huludao Power Supply Company, Huludao, 125000, China
4.State Grid Liaoning Electric Power Co. Ltd., Anshan Power Supply Company, Anshan, 114014, China
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Wang ZF,Yu, Haifei,Hu, Bo,et al. Research on early warning of electric power customers' credit risk based on SVM[C]//Dalian University of Technology, Systems Engineering Society of China (SESC), Technical Committee on Control Theory (TCCT), Chinese Association of Automation (CAA). Piscataway, NJ, USA:IEEE Computer Society,2017:10209-10213.
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