Fuzzy Modeling in Some Reduction Methods of Inference Rules(Nonlinear Problems)(Regular Section)
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概要
- 論文の詳細を見る
This paper is concerned with fuzzy modeling in some reduction methods of inference urles with gradient descent. Reduction methods are presented, which have a reduction mechanism of the rule unit that is applicable in three parameters-the central value and the width of the membership function in the antecedent part, and the real number in the consequent part-which constitute the standard fuzzy system. In the present techniques, the necessary number of rules is set beforehand and the rules are sequentially deleted to the prespecified number. These methods indicate that techniques other than the reduction approach introduced previously exist. Experimental results are presented in order to show that the effectiveness differs between the proposed techniques according to the average inference error and the number of learning iterations.
- 社団法人電子情報通信学会の論文
- 2001-03-01
著者
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MAEDA Michiharu
Department of Computer Science and Engineering, Faculty of Information Engineering, Fukuoka Institut
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Miyajima Hiromi
Faculty Of Engineering Kagoshima University
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