Hybrid approach for fuzzy system design

Ying Li, Rongchun Zhao, Yanning Zhang, Licheng Jiao

Research output: Contribution to journalArticlepeer-review

Abstract

A hybrid approach for fuzzy system design based on clustering and a kind of neurofuzzy networks is proposed. An unsupervised clustering technique is firstly used to determine the number of if-then fuzzy rules and generate an initial fuzzy rule base from the given input-output data. Then, a class of neurofuzzy networks is constructed and its weights are tuned so that the obtained fuzzy rule base has a high accuracy. Finally, two examples of function approximation problems are given to illustrate the effectiveness of the proposed approach.

Original languageEnglish
Pages (from-to)299-303
Number of pages5
JournalJournal of Systems Engineering and Electronics
Volume15
Issue number3
StatePublished - Sep 2004

Keywords

  • Clustering
  • Fuzzy rule base
  • Fuzzy systems design
  • Neurofuzzy networks

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