Adaptive arrangement classifier via neuro-fuzzy modeling

研究成果: Paper査読

抄録

A hybrid fuzzy-neuro classifier that extracts rules in terms of polyhedrons in the input space is proposed. The network uses a fuzzy disjunctive normal form in its hidden layer to effectively map polyhedral regions, which are gradually adjusted during learning, to category labels. The major advantage of the present method lies in that it is quite simple in architecture, every layer enjoys a clear fuzzy logical interpretation, and the number of rules needed is very few. The results of classification experiments seem to be quite promising.

本文言語English
ページ577-580
ページ数4
出版ステータスPublished - 2000 1 1
イベントFUZZ-IEEE 2000: 9th IEEE International Conference on Fuzzy Systems - San Antonio, TX, USA
継続期間: 2000 5 72000 5 10

Other

OtherFUZZ-IEEE 2000: 9th IEEE International Conference on Fuzzy Systems
CitySan Antonio, TX, USA
Period00/5/700/5/10

ASJC Scopus subject areas

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

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