Self-Organized Similarity based Kernel Fuzzy Clustering Model and Its Applications
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The purpose of this paper is to improve the performance of the kernel fuzzy clustering model by introducing a self-organized algorithm. A conventional kernel fuzzy clustering model is defined as a model which is an improved additive fuzzy clustering. The purpose of this conventional model is to obtain a clearer result by consideration of the interaction of clusters. This paper proposes a fuzzy clustering model based on the idea of self-organized dissimilarity between two objects.
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
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IEEE SMC Hiroshima Chapter
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Graduate School of Engineering