Mountain Clustering Based on Improved PSO Algorithm
SHEN HongYuan1,2, PENG XiaoQi1, WANG JunNian2,3, HU ZhiKun3
1.Institute of Energy and Power Engineering, Central South University, Changsha 410083 2.Institute of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201 3.Institute of Information Science and Engineering, Central South University, Changsha 410083
Abstract The PSO (particle swarm optimization) algorithm is reformed so that it can be used in multimodel function optimization. The improved PSO is combined with a mountain clustering method. A mountain clustering based on improved PSO (MCBIPSO) algorithm is presented. The principle and steps are supplied in this paper. The simulation results show that the mechanism of the MCBIPSO algorithm is definite. When the MCBIPSO algorithm is used in clustering based on density, the calculation is easier and more efficient in deciding the clustering centers of data samples. The MCBIPSO algorithm can realize accuracy clustering based on the samples density.
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2006, Vol. 19 
