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.
|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 26 → 1994 6月 29
|Other||Proceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3)|
|City||Orlando, FL, USA|
|Period||94/6/26 → 94/6/29|
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