AN IMPROVED LEARNING OF LOCAL SEARCH FOR FUZZY CONTROLLER NETWORK

被引：0

作者：

Vairappan, Catherine ^{[1
]}

Gao, Shangce ^{[1
]}

Tamura, Hiroki ^{[2
]}

Tang, Zheng ^{[1
]}

机构：

[1] Toyama Univ, Fac Engn, Toyama 9308555, Japan

[2] Miyazaki Univ, Fac Engn, Miyazaki 8892192, Japan

来源：

INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL | 2009年 / 5卷 / 04期

关键词：

Fuzzy controller; Local search; Back propagation; NEURAL-NETWORKS; CONTROL-SYSTEMS; IDENTIFICATION; BACKPROPAGATION; DESIGN; MODEL;

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：

In this paper, we propose an improved version of local search learning for a fuzzy controller network. Local search learning has a reputation for fast, convergence and straightforward. However premature convergence makes it unsuitable for optimization problems. Comparison with temporal back propagation and canonical local search showed that the proposed method converges faster and is suitable for fuzzy controller problem.

引用

页码：1101 / 1113

页数：13