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Titulo: Automatic Recurrent and Feed-Forward ANN Rule and Expression Extraction with Genetic Programming
Tipo: revista internacional
Fecha: 9,2002
Revista: Lecture Notes in Computer Science. Parallel Problem Solving from Nature
JCR Journal; Impact Factor: 0.402
Volumen: LNCS 2439
Paginas: 485-494
ISSN: 0302-9743
ISBN: 3-540-44139-5
Editorial: Springer- Verlag
Berlín (Alemania)


Various rule-extraction techniques using ANN have been used so far, most of them being applied on multi-layer ANN, since they are more easily handled. In many cases, extraction methods focusing on different types of networks and training have been impemented. However, there are virtually no methods that view the extraction of rules from Ann as systems wich are independent from their architecture, training and internal distribution of weights, connections and activation functions. This paper proposes a rule-extraction system of ANN regardless of their architecture (multi-layer or recurrent), using Genetic Programming as a rule-exploration technique.

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