A selforganizing neural-network-based fuzzy system

被引：0

作者：

Wang, Y ^{[1
]}

Rong, G ^{[1
]}

机构：

[1] Zhejiang Univ, Inst Ind Process Control, Hangzhou 310027, Peoples R China

来源：

FIFTH INTERNATIONAL CONFERENCE ON ARTIFICIAL NEURAL NETWORKS | 1997年 / 440期

关键词：

fuzzy logic; neural network; nearest neighborhood clustering scheme; back-propagation learning scheme;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present in this paper a neural-network-based fuzzy system. It is a self-organizing neural-network. By combining both nearest neighborhood clustering sad back-propagation learning scheme, it can be trained to develop fuzzy logic rules and find optimal fuzzy membership functions. Simulation results suggest that the method has merits of simple structure, fast learning speed and good modeling accuracy.

引用

页码：106 / 110

页数：5

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