Research on early warning of electric power customers' credit risk based on SVM

被引：0
|
作者：
Wang, Zhongfeng [1 ]
Yu, Haifei [2 ]
Hu, Bo [3 ]
Zhang, Tao [4 ]
Lv, Bo [2 ]
机构：
[1] Chinese Acad Sci, Shenyang Inst Automat, Shenyang 110016, Liaoning, Peoples R China
[2] Northeastern Univ, Coll Business Adm, Shenyang 110169, Liaoning, Peoples R China
[3] Huludao Power Supply Co, State Grid Liaoning Elect Power Co Ltd, Huludao 125000, Peoples R China
[4] Anshan Power Supply Co, State Grid Liaoning Elect Power Co Ltd, Anshan 114014, Peoples R China
来源：
PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017) | 2017年
关键词：
SVM; credit risk; early-warning model; power market; SUPPORT VECTOR MACHINES; PREDICTION;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
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.
引用
收藏
页码：10209 / 10213
页数：5
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