Revistes Catalanes amb Accés Obert (RACO)

Neural methods for obtaining fuzzy rules

José Manuel Benítez Sánchez, Armando Blanco Morón, Miguel Delgado Calvo-Flores, Ignacio Requena Ramos


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

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