Automatic Clustering Based on GA-FCM for Pattern Recognition

被引：7

作者：

Gao, Yunguang ^{[1
]}

Wang, Shicheng ^{[1
]}

Liu, Shunbo ^{[1
]}

机构：

[1] Hong Qing High Tech Inst, Lab 301, Xian, Peoples R China

来源：

SECOND INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN, VOL 2, PROCEEDINGS | 2009年

关键词：

pattern recognition; fuzzy c-means clustering; genetic algorithm; initial clsssification number; local minimum;

D O I：

10.1109/ISCID.2009.184

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Aiming to the shortages of fuzzy c-means clustering applied to pattern recognition, an improved method by genetic algorithm is proposed. This method can not only automatically optimizes the classification number, but also search the global optimal solution for the clustering center. The experimental results demonstrate this proposed method is excellent for pattern recognition.

引用

页码：146 / 149

页数：4

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