Abstract
In this paper, a new clustering algorithm based on 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 squared-error criterion. The simulation results indicate that the proposed algorithm produces clusters with acceptable quality with respect to squared-error criteria and provides a performance that is significantly superior to that of the K-means algorithm.
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Rastegar, R., Rahmati, M., Meybodi, M.R. (2005). A Clustering Algorithm using Cellular Learning Automata based Evolutionary Algorithm. In: Ribeiro, B., Albrecht, R.F., Dobnikar, A., Pearson, D.W., Steele, N.C. (eds) Adaptive and Natural Computing Algorithms. Springer, Vienna. https://doi.org/10.1007/3-211-27389-1_35
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DOI: https://doi.org/10.1007/3-211-27389-1_35
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