Destructive Fuzzy Modeling Using Neural Gas Network
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概要
- 論文の詳細を見る
In order to construct fuzzy systems automatically, there are many studies on combining fuzzy inference with neural networks. In these studies, fuzzy models using self-organization and vector quantization have been proposed. It is well known that these models construct fuzzy inference rules effectively representing distribution of input data, and not affected by increment of input dimensions. In this paper, we propose a destructive fuzzy modeling using neural gas network and demonstrate the validity of a proposed method by performing some numerical examples.
- 社団法人電子情報通信学会の論文
- 1997-09-25
著者
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MIYAJIMA Hiromi
the Faculty of Engineering, Kagoshima University
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KISHIDA Kazuya
the Faculty of Engineering, Kagoshima University
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Maeda M
Department Of Computer Science And Engineering Faculty Of Information Engineering Fukuoka Institute
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MAEDA Michiharu
the Department of Control & Information Systems Engineering at Kurume National College of Technology
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Kishida Kazuya
The Faculty Of Engineering Kagoshima University
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Maeda Michiharu
The Department Of Control & Information Systems Engineering At Kurume National College Of Techno
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Miyajima Hiromi
The Faculty Of Engineering Kagoshima University
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