Constructing hierarchical fuzzy rule bases for classification

Tamás D. Gedeon, Kok Wai Wong, Domonkos Tikk

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Fuzzy rule based systems have been very popular in many control applications. However, when fuzzy control systems are used in real problems, many rules may be required. The number of rules required depends on the number of inputs and the number of fuzzy linguistic terms used. This exponential explosion of fuzzy rules can take too much computing time to solve any but the simplest problems. This paper proposes a hierarchical fuzzy system that partitions a problem for more efficient computation. The hierarchical fuzzy rule base algorithm constructs rules from data for the purpose of performing fuzzy classification. Illustration examples are also generated and the results show that this hierarchical fuzzy system can be successfully used for classification applications.

Original languageEnglish
Article number86
Pages (from-to)1388-1391
Number of pages4
JournalIEEE International Conference on Fuzzy Systems
Volume3
DOIs
Publication statusPublished - Jan 1 2001

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

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