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 journalArticlepeer-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 languageEnglish
Pages (from-to)881-892
Number of pages12
JournalJournal of Intelligent and Fuzzy Systems
Volume25
Issue number4
DOIs
Publication statusPublished - 2013 Jan 1

All Science Journal Classification (ASJC) codes

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

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