Neural methods for obtaining fuzzy rules

In previous papers, we presented an empirical methodology based on Neural Networks for obtaining fuzzy rules which allow a system to be described, using a set of examples with the corresponding inputs and outputs. Now that the previous results have been completed, we present another procedure for ob...

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Bibliographic Details
Main Authors Benítez Sánchez, José Manuel, Blanco Morón, Armando, Delgado Calvo-Flores, Miguel, Requena Ramos, Ignacio
Format Journal Article
LanguageCatalan
Published 1996
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Summary:In previous papers, we presented an empirical methodology based on Neural Networks for obtaining fuzzy rules which allow a system to be described, using a set of examples with the corresponding inputs and outputs. Now that the previous results have been completed, we present another procedure for obtaining fuzzy rules, also based on Neural Networks with Backpropagation, with no need to establish beforehand the labels or values of the variables that govern the system
ISSN:1134-5632
1989-533X