Fuzzy inference neural networks which automatically partition a pattern space and extract fuzzy if - then rules

Takatoshi Nishina, Masafumi Hagiwara, Masao Nakagawa

研究成果: Paper査読

4 被引用数 (Scopus)

抄録

This paper proposes Fuzzy Inference Neural Networks (FINNs) which automatically partition a pattern space and extract fuzzy if-then rules from numerical data. There are three distinctive features in our model: 1) the membership functions of the fuzzified part are constructed in the connection between the input-part and the rule-layer; 2) Kohonen's self-organizing algorithm is applied to partition the input-output space. Consequently, they can extract polished fuzzy if-then rules; 3) they can adapt the number of rules automatically. We deal with two illustrative examples: 1) fuzzy control of unmanned vehicle; 2) prediction of the trend of stock prices. Computer simulation results indicate the effectiveness of the proposed FINNs.

本文言語English
ページ1314-1319
ページ数6
出版ステータスPublished - 1994 12月 1
イベントProceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3) - Orlando, FL, USA
継続期間: 1994 6月 261994 6月 29

Other

OtherProceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3)
CityOrlando, FL, USA
Period94/6/2694/6/29

ASJC Scopus subject areas

  • ソフトウェア
  • 理論的コンピュータサイエンス
  • 人工知能
  • 応用数学

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