摘要
事先预知电力客户欠费的可能性,变事后管理模式为事前管理模式,可有效减少电力公司在营销过程中,因电费可能被拖欠而引发的经营风险。在对实际电力客户欠费原因分析的基础上,找出导致电费拖欠的主要因素,分析它们之间的关系,建立基于电力客户欠费特征变量的灰色系统预警模型,并采用灰色聚类算法,对预测出来的表征电力客户欠费特征的数据进行分类判断,从而可事先清楚该客户的类别,为电力公司从营销角度细分客户市场,制定不同的信用管理对策提供依据。
In the process of electricity sales, it is important for power company to know the default probability of electricity fees by power clients, which would decrease the default risk greatly; forewarning is a new technology in which previous post-mortem management can be turned into a priority one. Based on the analysis of complicated reasons of default, the key impacting factors as well as theirs effect on default is found, the forewarning model is established by means of theory of grey system predication, and a group of predicted feature variables is gotten; then, by the grey cluster algorithm, the problem of client category could be determined, which is valuable for power company to subdivision the clients market and make out the different credit management strategies.
出处
《中国电机工程学报》
EI
CSCD
北大核心
2008年第22期107-112,共6页
Proceedings of the CSEE
关键词
电力营销
信用指标
欠费预警
灰色系统预测
灰色聚类
市场细分
electricity sales
credit indices
arrears forewarn
grey system predication model
grey cluster
market subdivision
