Development and Optimization of Fuzzy Control System based on Self-Organizing Neural Network and Rough Set Theory

被引：0
|
作者：
Tanaka, Hiroto [1 ]
机构：
[1] Hirosaki Univ, Hirosaki, Aomori, Japan
来源：
INTERNATIONAL SYMPOSIUM 2015: MECHANICAL AND ELECTRONICAL SYSTEMS AND CONTROL ENGINEERING | 2015年
关键词：
Fuzzy Control; Self-Organizing; Neural Network; Rough Set Theory; Optimization;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we conduct research on the development and optimization of fuzzy control system based on the self-organizing neural network and the rough set theory. Fuzzy control system according to the engineering application of the vast majority of basic common characteristics of the input variable of fuzzy membership functions and clearly defines the fuzzy control system for double overlapping fuzzy partition of the input variables, and studied the input variables with the double overlapping fuzzy partition of the nature of the fuzzy control system. The method makes full use of the fuzzy rules before a fuzzy membership function of input variable structure information, reduced the limitations of previous stability determination method and the difficulty. The experimental result verifies the feasibility of our proposed method.
引用
收藏
页码：123 / 128
页数：6
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