Title :
A fuzzy clustering algorithm using cellular learning automata based evolutionary algorithm
Author :
Rastegar, R. ; Arasteh, A.R. ; Hariri, A. ; Meybodi, M.R.
Author_Institution :
Comput. Eng. Dept., Amirkabir Univ. of Technol., Tehran, Iran
Abstract :
In this paper, a new fuzzy clustering algorithm that uses cellular learning automata based evolutionary computing (CLA-EC) is proposed. The CLA-EC is a model obtained by combining the concepts of cellular learning automata and evolutionary algorithms. The CLA-EC is used to search for cluster centers in such a way that minimizes the clustering criterion. The simulation results indicate that the proposed algorithm produces clusters with acceptable quality with respect to clustering criterion and provides a performance that is superior to that of the C-means algorithm.
Keywords :
cellular automata; learning (artificial intelligence); learning automata; pattern clustering; cellular learning automata; evolutionary computing; fuzzy clustering algorithm; Clustering algorithms; Clustering methods; Computational modeling; Equations; Euclidean distance; Evolutionary computation; Fuzzy sets; Learning automata; Mathematical model; Prototypes;
Conference_Titel :
Hybrid Intelligent Systems, 2004. HIS '04. Fourth International Conference on
Print_ISBN :
0-7695-2291-2
DOI :
10.1109/ICHIS.2004.3
