ID | 19653 |
Eprint ID | 19653
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FullText URL | |
Author |
Kuwata Tomoyuki
Sato-Ilic Mika
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Abstract | 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.
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Published Date | 2009-11-11
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Publication Title |
Proceedings : Fifth International Workshop on Computational Intelligence & Applications
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Volume | volume2009
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Issue | issue1
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Publisher | IEEE SMC Hiroshima Chapter
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Start Page | 127
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End Page | 131
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ISSN | 1883-3977
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NCID | BB00577064
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Content Type |
Conference Paper
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language |
English
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Copyright Holders | IEEE SMC Hiroshima Chapter
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Event Title | 5th International Workshop on Computational Intelligence & Applications IEEE SMC Hiroshima Chapter : IWCIA 2009
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Event Location | 東広島市
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Event Location Alternative | Higashi-Hiroshima City
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File Version | publisher
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Refereed |
True
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Eprints Journal Name | IWCIA
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