A mountain clustering based on improved PSO algorithm

被引：0
|
作者：
Shen, HY [1 ]
Peng, XQ
Wang, JN
Hu, ZK
机构：
[1] Cent S Univ, Inst Energy & Power Engn, Changsha 410083, Peoples R China
[2] Hunan Univ Sci & Technol, Inst Informat & Elect Engn, Xiangtan 411201, Peoples R China
[3] Cent S Univ, Inst Informat Sci & Engn, Changsha 410083, Peoples R China
来源：
ADVANCES IN NATURAL COMPUTATION, PT 3, PROCEEDINGS | 2005年 / 3612卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In order to find most centre of the density of the sample set this paper combines MCA and PSO, and presents a mountain clustering based on improved PSO (MCBIPSO) algorithm. A mountain clustering method constructs a mountain function according to the density of the sample, but it is not easy to find all peaks of the mountain function. The improved PSO algorithm is used to find all peaks of the mountain function. The simulation results show that the MCBIPSO algorithm is successful in deciding the density clustering centers of data samples.
引用
收藏
页码：477 / 481
页数：5
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