Browsing by Author "Requena Ramos, Ignacio"
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A methodology for constructing fuzzy rule based classification systems
Fernández Garrido, José María; Requena Ramos, Ignacio (Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica, 2000)
Article
Open AccessIn this paper, a methodology to obtain a set of fuzzy rules for classification systems is presented. The system is represented in a layered fuzzy network, in which the links from input to hidden nodes represents the ... -
Max-Min fuzzy neural networks for solving relational equations
Blanco Morón, Armando; Delgado Calvo-Flores, Miguel; Requena Ramos, Ignacio (Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica, 1994)
Article
Open AccessThe Relational Equations approach is one of the most usual ones for describing (Fuzzy) Systems and in most cases, it is the final expression for other descriptions. This is why the identification of Relational Equations ... -
Neural methods for obtaining fuzzy rules
Benítez Sánchez, José Manuel; Blanco Morón, Armando; Delgado Calvo-Flores, Miguel; Requena Ramos, Ignacio (Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica, 1996)
Article
Open AccessIn 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 ... -
New aspects on extraction of fuzzy rules using neural networks
Benítez Sánchez, José Manuel; Blanco Morón, Armando; Delgado Calvo-Flores, Miguel; Requena Ramos, Ignacio (Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica, 1998)
Article
Open AccessIn previous works, we have presented two methodologies to obtain fuzzy rules in order to describe the behaviour of a system. We have used Artificial Neural Netorks (ANN) with the {\it Backpropagation} algorithm, and a set ...