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Artificial Immune System Clustering Algorithm and Electricity Customer Credit Analysis

  • Shu-xia Yang
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 56)

Abstract

The real encoding artificial immune system cluster analysis process was put forward firstly, and then the electricity customer credit analysis indexes were determined. At last, according to the customer data of a power company, it classified the electricity customer credit into high, medium and low three categories, and there were two customers with high credit, three customers with medium credit, and one customer with low credit. The results show that the artificial immune system cluster analysis method can obtain the solution once the concentration threshold and cluster number is determined, and its calculation is relatively simple. This method can minimize the requirements of professional knowledge and it is suitable to large volume of data while it is not sensitive to the different data order at the same time. So the artificial immune system cluster analysis has many advantages in obtaining the optimal solution, and this method is feasible to be used in cluster analysis.

Keywords

artificial immune system cluster customer credit 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Shu-xia Yang
    • 1
  1. 1.School of Business AdministrationNorth China Electric Power UniversityBeijingChina

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