An improved generalized fuzzy c-means clustering algorithm based on GA

Authors:
Wenping Ma;Xiaohua Ge;Licheng Jiao
Affiliations:
Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, P.R. China;Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, P.R. China;Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, P.R. China
Venue:
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Year:
2011

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Abstract

A new generalized clustering algorithm with the name of genetic algorithm based rough-fuzzy possibilistic c-means (GARFPCM) is proposed. It derives from an unsupervised learning algorithm called RFPCM, which is unstable for the reason of random initialization. GA is introduced into RFPCM to generate an improved version, which is GARFPCM mentioned above. GARFPCM can obtain better clustering quality. Through performance evaluation on image segmentation, GARFPCM is shown to perform excellently.