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13.660 Articles in journals published by the UPC
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  • 1996, Vol. III, Núm. 3
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Neural methods for obtaining fuzzy rules

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Benítez Sánchez, José Manuel
Blanco Morón, Armando
Delgado Calvo-Flores, Miguel
Requena Ramos, Ignacio
Document typeArticle
Defense date1996
PublisherUniversitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
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
CitationUniversitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica 
URIhttp://hdl.handle.net/2099/3475
ISSN1134-5632
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  • Mathware & soft computing - 1996, Vol. III, Núm. 3 [13]
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