Research of Electricity Customer Classifications Based on Kernel Clustering Algorithm under the Organic Combined Model

Abstract:

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The principle of kernel methods combined with data description were analyzed and the organic combined model of particle swarm algorithm(PSO) and genetic algorithm(GA) was put forward firstly, then the kernel clustering algorithm under the organic combined model of the GA and the PSO was put forward. Finally, according to the customers’ data of certain electric power company, this kernel clustering algorithm was applied to classify the electricity customers into three groups: the first group includes 3 customers, 5 and 7 customers for the second group and the third group respectively. The result shows that the samples can be classified and the center of mass can be obtained using the data description based on kernel methods. But the clustering region is different when the of kernel method gets the different value. This makes the clustering process to be complex, also spends the longer time. While kernel method’s clustering algorithm organically combined with the PSO and GA can get the same result in the shorter time and the calculation is simpler

Info:

Periodical:

Edited by:

Dongye Sun, Wen-Pei Sung and Ran Chen

Pages:

4570-4574

DOI:

10.4028/www.scientific.net/AMM.121-126.4570

Citation:

S. X. Yang and H. Ding, "Research of Electricity Customer Classifications Based on Kernel Clustering Algorithm under the Organic Combined Model", Applied Mechanics and Materials, Vols. 121-126, pp. 4570-4574, 2012

Online since:

October 2011

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$35.00

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