Optimization of the Fuzzy C-Means Algorithm using Evolutionary Methods

被引：0
|
作者：
Castillo, Oscar [1 ]
Rubio, Elid [1 ]
Soria, Jose [1 ]
Naredo, Enrique [1 ]
机构：
[1] Tijuana Inst Technol, Tijuana, Mexico
来源：
ENGINEERING LETTERS | 2012年 / 20卷 / 01期
关键词：
Cluster validity; clustering number; comparison between methods; genetic algorithms; optimization; and 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 presents the optimization of the Fuzzy C-Means algorithm by evolutionary or bio-inspired methods, this in order to automatically find the optimal number of clusters and the weight exponent. Optimization methods used to realization of this paper were genetic algorithms and particle swarm optimization. The results obtained by both methods are presented, and a comparison between both methods to observe if one method is better than the other.
引用
收藏
页码：61 / 67
页数：7
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