A methodology for constructing fuzzy rule-based classification systems.

José María Fernández Garrido; Ignacio Requena Ramos

Mathware and Soft Computing (2000)

  • Volume: 7, Issue: 2-3, page 185-197
  • ISSN: 1134-5632

Abstract

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In 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 antecedents of the rules, and the consequents are represented by links from hidden to output nodes. Specific genetic algorithms are used in two phases to extract the rules. In the first phase an initial version of the rules is extracted, and in second one, the labels are refined. The procedure is illustrated by applying it to two real-world classification problems.

How to cite

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Fernández Garrido, José María, and Requena Ramos, Ignacio. "A methodology for constructing fuzzy rule-based classification systems.." Mathware and Soft Computing 7.2-3 (2000): 185-197. <http://eudml.org/doc/39198>.

@article{FernándezGarrido2000,
abstract = {In 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 antecedents of the rules, and the consequents are represented by links from hidden to output nodes. Specific genetic algorithms are used in two phases to extract the rules. In the first phase an initial version of the rules is extracted, and in second one, the labels are refined. The procedure is illustrated by applying it to two real-world classification problems.},
author = {Fernández Garrido, José María, Requena Ramos, Ignacio},
journal = {Mathware and Soft Computing},
keywords = {Clasificación; Conjuntos difusos; Algoritmos genéticos; Inteligencia artificial; fuzzy rules; fuzzy network},
language = {eng},
number = {2-3},
pages = {185-197},
title = {A methodology for constructing fuzzy rule-based classification systems.},
url = {http://eudml.org/doc/39198},
volume = {7},
year = {2000},
}

TY - JOUR
AU - Fernández Garrido, José María
AU - Requena Ramos, Ignacio
TI - A methodology for constructing fuzzy rule-based classification systems.
JO - Mathware and Soft Computing
PY - 2000
VL - 7
IS - 2-3
SP - 185
EP - 197
AB - In 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 antecedents of the rules, and the consequents are represented by links from hidden to output nodes. Specific genetic algorithms are used in two phases to extract the rules. In the first phase an initial version of the rules is extracted, and in second one, the labels are refined. The procedure is illustrated by applying it to two real-world classification problems.
LA - eng
KW - Clasificación; Conjuntos difusos; Algoritmos genéticos; Inteligencia artificial; fuzzy rules; fuzzy network
UR - http://eudml.org/doc/39198
ER -

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