Research of Evaluating Credit-Risk in Power Enterprise Based on SVM and VIKOR Method
被引:1
作者:
Huang, Yuansheng
论文数: 0引用数: 0
h-index: 0
机构:
N China Elect Power Univ, Dept Econ & Management, Baoding, Peoples R ChinaN China Elect Power Univ, Dept Econ & Management, Baoding, Peoples R China
Huang, Yuansheng
[1
]
Yan, Ying
论文数: 0引用数: 0
h-index: 0
机构:
N China Elect Power Univ, Dept Econ & Management, Baoding, Peoples R ChinaN China Elect Power Univ, Dept Econ & Management, Baoding, Peoples R China
Yan, Ying
[1
]
机构:
[1] N China Elect Power Univ, Dept Econ & Management, Baoding, Peoples R China
来源:
IEEM: 2008 INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT, VOLS 1-3
|
2008年
Some clients are in arrears with a great amount of electricity charges in operation of power system, which has seriously hindered the healthy development of Electric Industry. Evaluation of clients' credit is an important problem of management in Power Supply Enterprises. Considering the training time and the accuracy, a new algorithm based on Support Vector Machine (SVM) and VIKOR method is adopted to solve this problem. Support Vector Machine (SVM) was proposed to solve the small sample learning problem. VIKOR method was developed to solve decision problems with conflicting and with different units criteria. Finally, an application example has been given to test the feasibility and effectiveness of the proposed method.
引用
收藏
页码:1596 / 1599
页数:4
相关论文
共 5 条
[1]
Du Shu-xin, 2003, Journal of Zhejiang University, V37, P521