Development of a rule selection mechanism by using neuro-fuzzy methodology for structural vibration suppression

被引：6

作者：

Chen, Chuen-Jyh ^{[1
]}

Yang, Shih-Ming ^{[2
]}

Chen, Chu-Yun ^{[2
]}

机构：

[1] Aletheia Univ, Dept Air Transportat Management, Tainan 721, Taiwan

[2] Natl Cheng Kung Univ, Dept Aeronaut & Astronaut, Tainan 70101, Taiwan

来源：

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | 2013年 / 25卷 / 04期

关键词：

Rule selection; membership function; neural network; fuzzy logic; SYSTEM; NETWORK;

D O I：

10.3233/IFS-120691

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The development of neuro-fuzzy systems by integrating neural networks and fuzzy systems is desired because such systems can adjust fuzzy membership functions and produce fuzzy inference rules by case-learning without the need for experts or experiments. It has been applied to various fields, but there has been no detailed study of the various neuro-fuzzy models applicable to rule generation. In this paper, an experimentally verified five-layer and three-phase network is presented, which shows the effectiveness with which the neuro-fuzzy system automatically determines membership functions and selects activation fuzzy rules using both system identification and vibration control examples in engineering applications.

引用

页码：881 / 892

页数：12

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