Complexity management methodology for fuzzy systems with feedback rule bases

Alexander Gegov, David Sanders, Boriana Vatchova

Research output: Contribution to journalArticlepeer-review

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Abstract

This paper proposes a complexity management methodology for fuzzy systems with feedback rule bases. The methodology is based on formal methods for presentation, manipulation and transformation of fuzzy rule bases. First, Boolean matrices are used for formal presentation of rule bases. Then, binary merging operations are used for formal manipulation of rule bases. Finally, repetitive merging operations are used for formal transformation of rule bases. The formal methods facilitate the understanding and modelling of fuzzy systems in terms of interacting subsystems. In particular, the methods reduce the qualitative complexity in fuzzy systems by improving the transparency of the rule bases.
Original languageEnglish
Pages (from-to)451-464
Number of pages14
JournalJournal of Intelligent & Fuzzy Systems
Volume26
Issue number1
Early online date11 Jun 2013
DOIs
Publication statusPublished - 2014

Keywords

  • fuzzy systems
  • complexity management
  • formal methods
  • rule bases
  • fuzzy networks

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