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

Chuen Jyh Chen; Shih Ming Yang; Chu Yun Chen

doi:10.3233/IFS-120691

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

Chuen Jyh Chen, Shih Ming Yang, Chu Yun Chen

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

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.

Original language	English
Pages (from-to)	881-892
Number of pages	12
Journal	Journal of Intelligent and Fuzzy Systems
Volume	25
Issue number	4
DOIs	https://doi.org/10.3233/IFS-120691
Publication status	Published - 2013 Jan 1

All Science Journal Classification (ASJC) codes

Statistics and Probability
Engineering(all)
Artificial Intelligence

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

Abstract

All Science Journal Classification (ASJC) codes

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