### Abstract

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.

Original language | English |
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Pages | 1314-1319 |

Number of pages | 6 |

Publication status | Published - 1994 Dec 1 |

Event | Proceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3) - Orlando, FL, USA Duration: 1994 Jun 26 → 1994 Jun 29 |

### Other

Other | Proceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3) |
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City | Orlando, FL, USA |

Period | 94/6/26 → 94/6/29 |

### ASJC Scopus subject areas

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

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## Cite this

*Fuzzy inference neural networks which automatically partition a pattern space and extract fuzzy if - then rules*. 1314-1319. Paper presented at Proceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3), Orlando, FL, USA, .