Self-Organized Similarity based Kernel Fuzzy Clustering Model and Its Applications
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
Page 127-131
published_at 2009-11
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| File | |
| Title ( eng ) |
Self-Organized Similarity based Kernel Fuzzy Clustering Model and Its Applications
|
| Creator |
Kuwata Tomoyuki
Sato-Ilic Mika
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| Source Title |
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
|
| Start Page | 127 |
| End Page | 131 |
| 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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| NDC |
Technology. Engineering [ 500 ]
|
| Language |
eng
|
| Resource Type | conference paper |
| Publisher |
IEEE SMC Hiroshima Chapter
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| Date of Issued | 2009-11 |
| Rights |
(c) Copyright by IEEE SMC Hiroshima Chapter.
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| Publish Type | Version of Record |
| Access Rights | open access |
| Source Identifier |
[ISSN] 1883-3977
[URI] http://www.hil.hiroshima-u.ac.jp/iwcia/2009/
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