DocumentCode
2905093
Title
Automatic Clustering Based on GA-FCM for Pattern Recognition
Author
Gao, Yunguang ; Wang, Shicheng ; Liu, Shunbo
Author_Institution
301 Lab., Hong Qing High-tech Inst., Xi´´an, China
Volume
2
fYear
2009
fDate
12-14 Dec. 2009
Firstpage
146
Lastpage
149
Abstract
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.
Keywords
fuzzy set theory; genetic algorithms; pattern clustering; GA-FCM; automatic clustering; fuzzy c-means clustering; genetic algorithm; pattern recognition; Application software; Artificial intelligence; Clustering algorithms; Computational intelligence; Evolution (biology); Fuzzy sets; Genetic algorithms; Optimization methods; Pattern recognition; Uncertainty; fuzzy c-means clustering; genetic algorithm; initial classification number; local minimum; pattern recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Design, 2009. ISCID '09. Second International Symposium on
Conference_Location
Changsha
Print_ISBN
978-0-7695-3865-5
Type
conf
DOI
10.1109/ISCID.2009.184
Filename
5368729
Link To Document