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
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;
Conference_Titel :
Computational Intelligence and Design, 2009. ISCID '09. Second International Symposium on
Conference_Location :
Changsha
Print_ISBN :
978-0-7695-3865-5
DOI :
10.1109/ISCID.2009.184
