The adaptive dynamic clustering neuro-fuzzy system for classification

被引：5

作者：

Napook, Phichit ^{[1
]}

Eiamkanitchat, Narissara ^{[1
,2
]}

机构：

[1] Department of Computer Engineering, Chiang Mai University

[2] Social Research Institute, Chiang Mai University

来源：

Lecture Notes in Electrical Engineering | 2015年 / 339卷

关键词：

Adaptive Dynamic Clustering; Classification; Neuro-Fuzzy System;

D O I：

10.1007/978-3-662-46578-3_85

中图分类号：

学科分类号：

摘要：

This paper proposes a method of neuro-fuzzy for classification using adaptive dynamic clustering. The method has three parts, the first part is to find the proper number of membership functions by using adaptive dynamic clustering and transform to binary value in a second step. The final step is classification part using neural network. Furthermore the weights from the learning process of the neural network are used as feature eliminates to perform the rule extraction. The experiments used dataset form UCI to verify the proposed methodology. The result shows the high performance of the proposed method. © Springer-Verlag Berlin Heidelberg 2015.

引用

页码：721 / 728

页数：7

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