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Rule insertion and rule extraction from evolving fuzzy neural networks: algorithms and applications for building adaptive, intelligent expert systems

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2 Author(s)
Kasabov, N. ; Dept. of Inf. Sci., Otago Univ., Dunedin, New Zealand ; Woodford, B.

Discusses the concept of intelligent expert systems and suggests tools for building an adaptable, in an online or in an off-line mode, rule base during the system operation in a changing environment. It applies evolving fuzzy neural networks (EFuNNs) as associative memories for the purpose of dynamic storing and modifying a rule base. Algorithms for rule extraction and rule insertion from EFuNNs are explained and applied to a case study using gas furnace data and the iris data set.

Published in:

Fuzzy Systems Conference Proceedings, 1999. FUZZ-IEEE '99. 1999 IEEE International  (Volume:3 )

Date of Conference:

22-25 Aug. 1999