基于人工免疫系统聚类算法的用电客户信用分析

在分析人工免疫系统聚类算法的基础上研究基于人工免疫系统聚类算法的用电客户信用分析原理,建立用电客户信用分析指标体系,根据电力公司客户数据,采用人工免疫系统聚类分析方法对用电客户信用进行分析,将用电客户信用按高、中、低三类进行聚类,经计算得到信用高、中、低的用电客户分别为2家、3家、1家。结果表明人工免疫系统聚类分析方法只要确定了浓度阈值和聚类个数就可得到结果,计算过程简单,能够适用于大数据量,对专业知识的要求较低,对于数据的顺序不敏感,是一种进行用电客户信用分析的较好方法。

A Clustering Algorithm Based on Artificial Immune System and Electricity Customer Credit Analysis

The paper studies the clustering algorithm based on artificial immune system and electricity customer credit analysis theory on the basis of analyzing the artificial immune system clustering algorithm.Then it determines the indicators of electricity customers’ credit analysis,analyzes electricity customers’ credit based on the customer data of a power company by the artificial immune system cluster analysis method,categorizes electricity customer credit into three clusters by high,medium and low,obtains two electricity customers for the high electricity customer credit,three for the middle,and one for the low.The results show that the cluster analysis method based on immune system can obtain results if only defining concentration threshold and the number of clustering,it has a simple calculation,and can be applied to large volume of data,so that minimize the requirements for the expertise,and the method is not sensitive to different data orders.It is a good method for electricity customer credit analysis.