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 journalArticle

5 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 languageEnglish
Pages (from-to)881-892
Number of pages12
JournalJournal of Intelligent and Fuzzy Systems
Volume25
Issue number4
DOIs
Publication statusPublished - 2013

Fingerprint

Vibration Suppression
Neuro-fuzzy Systems
Selection Rules
Neuro-fuzzy
Fuzzy systems
Fuzzy Rules
Membership functions
Rule Generation
Fuzzy Membership Function
Vibration Control
Fuzzy Inference
Methodology
Inference Rules
Fuzzy Model
Engineering Application
System Identification
Membership Function
Fuzzy Systems
Activation
Fuzzy inference

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Engineering(all)
  • Artificial Intelligence

Cite this

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Development of a rule selection mechanism by using neuro-fuzzy methodology for structural vibration suppression. / Chen, Chuen Jyh; Yang, Shih-Ming; Chen, Chu Yun.

In: Journal of Intelligent and Fuzzy Systems, Vol. 25, No. 4, 2013, p. 881-892.

Research output: Contribution to journalArticle

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