摘要
考虑到电力公司对客户信息的管理数据以及企业信用管理的要求,设计了一套符合实际管理需要的、评估电力客户信用的指标体系,并采用人工神经网络理论,针对某电力公司的电力客户数据,建立了电力客户信用的判别分析模型,由于该模型的拟合精度高,所以当电力客户信用特征发生变化时,能有效地识别其所属的信用类型,从而使得电力公司能够预先知道哪些属于高信用风险的客户,达到防范信用风险的目的。
An index system that used artificial neural network theory to evaluate credit of electric power clients and met the practical management requirement was designed. According to the electric power client data of one electric power company, an identification and analysis model of electric power client credit was established. Because of its high fitting accuracy, the model can effectively identify the credit type of electric power clients when the credit characteristic of electric power clients changed, then electric power company could know in advance which clients had high credit risk, therefore avoiding credit risk.
出处
《湖南电力》
2006年第4期4-7,共4页
Hunan Electric Power
关键词
电力市场
信用风险
人工神经网络
判别模型
electric market
credit risk
artificial neural network
identify model
