Artificial Immune System Clustering Algorithm and Electricity Customer Credit Analysis
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.
Keywordsartificial immune system cluster customer credit
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- 3.Liu, W.: Research of data mining based on fuzzy clustering in comprehensive assessment. Mathematics in Practice and Theory 36(11), 88–92 (2006) (in Chinese)Google Scholar
- 4.Zuo, X., Ma, G.-w., Liang, W.-h., Wu, S.-y., Tu, Y.-j.: The forecast of electric power market voidance price bases on manpower immune system small wave network. Generate Electricity by Water 32(1), 13–158 (2006) (in Chinese)Google Scholar
- 5.Xie, G., Guo, H.-b., Xie, K.-m., Xu, X.-y., Chen, Z.-h.: The research and progress of artificial immune system algorithms. In: Proceedings of 6th International Symposium on Test and Measurement, vol. 7, pp. 6588–6591 (2005)Google Scholar
- 8.Liao, G.-C., Tsao, T.-P.: Application embedded chaos search immune genetic algorithm for short term unit commitment. Electric Power Systems Research (71), 135–144 (2004)Google Scholar
- 10.Liu, T., Wang, Y.-c., Wang, Z.-j.: One kind of cluster-algorithm bases on manpower immune system. Computer Project and Design 25(11), 2051–2053 (2004) (in Chinese)Google Scholar
- 13.Li, X., Yang, S.-x., Huang, C.-f.: Credit evaluation of electricity customers based on fuzzy multi-attribute decision making method. Power System Technology 28(21), 55–59 (2004) (in Chinese)Google Scholar
- 14.Wu, W.-t.: Analysis on credit rating to electricity customers. Beijing Chang Ping North China Electric Power University (2004) (in Chinese)Google Scholar
- 15.Wei, H.-l., Jiang, D.: Study of appraisal method of new product development project. Value Project (4) (2002) (in Chinese)Google Scholar
- 16.Wang, L., Yang, J., Xiong, S.-w.: An multi-objective optimization algorithm based on artificial immune system. Journal of Wuhan University of Technology 30(2), 116–118 (2008) (in Chinese)Google Scholar