Fuzzy Clustering methods Based on Modified PSO and Its Application

被引：0

作者：

Li, Xueyong ^{[1
]}

Gao, Guohong ^{[1
]}

Sun, Jiaxia ^{[1
]}

Miao, Guoyi ^{[1
]}

机构：

[1] Henan Inst Sci & Technol, Sch Informat Engineer, Xinxiang 453003, Peoples R China

来源：

INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL | 2011年 / 14卷 / 03期

关键词：

Particle swarm optimization (PSO); Fuzzy C-Mean (FCM); Clustering; intrusion detection system(IDS); PARTICLE SWARM OPTIMIZATION;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This paper proposed a new fuzzy clustering algorithm based on modified PSO. First separate solution space into smaller solution space, and then use goal function of Fuzzy C-mean as the faintness function of improved PSO, in order to obtain the sub-optimal solution as a chromosome of whole particle. Then search the global optimal solution. The grouped PSO Combining with FCM of processing can not only overcome the FCM's shortcomings of sensitive to the initial value, but also solve the PSO's problem of easy to fall into local optimal solution. Simulation results on real IDS dataset show the effectiveness of this algorithm.

引用

页码：925 / 930

页数：6

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