Fuzzy inference using a least square model.

Humberto Bustince; M. Calderón; Victoria Mohedano

Mathware and Soft Computing (1998)

  • Volume: 5, Issue: 2-3, page 141-149
  • ISSN: 1134-5632

Abstract

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In this paper, the method of least squares is applied to the fuzzy inference rules. We begin studying the conditions in which from a fuzzy set we can build another through the method of least squares. Then we apply this technique in order to evaluate the conclusions of the generalized modus ponens. We present different theorems and examples that demonstrate the fundamental advantages of the method studied.

How to cite

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Bustince, Humberto, Calderón, M., and Mohedano, Victoria. "Fuzzy inference using a least square model.." Mathware and Soft Computing 5.2-3 (1998): 141-149. <http://eudml.org/doc/39130>.

@article{Bustince1998,
abstract = {In this paper, the method of least squares is applied to the fuzzy inference rules. We begin studying the conditions in which from a fuzzy set we can build another through the method of least squares. Then we apply this technique in order to evaluate the conclusions of the generalized modus ponens. We present different theorems and examples that demonstrate the fundamental advantages of the method studied.},
author = {Bustince, Humberto, Calderón, M., Mohedano, Victoria},
journal = {Mathware and Soft Computing},
keywords = {Lógica difusa; Mínimos cuadrados; Modelos matemáticos; Inteligencia artificial; method of least squares; fuzzy inference rules},
language = {eng},
number = {2-3},
pages = {141-149},
title = {Fuzzy inference using a least square model.},
url = {http://eudml.org/doc/39130},
volume = {5},
year = {1998},
}

TY - JOUR
AU - Bustince, Humberto
AU - Calderón, M.
AU - Mohedano, Victoria
TI - Fuzzy inference using a least square model.
JO - Mathware and Soft Computing
PY - 1998
VL - 5
IS - 2-3
SP - 141
EP - 149
AB - In this paper, the method of least squares is applied to the fuzzy inference rules. We begin studying the conditions in which from a fuzzy set we can build another through the method of least squares. Then we apply this technique in order to evaluate the conclusions of the generalized modus ponens. We present different theorems and examples that demonstrate the fundamental advantages of the method studied.
LA - eng
KW - Lógica difusa; Mínimos cuadrados; Modelos matemáticos; Inteligencia artificial; method of least squares; fuzzy inference rules
UR - http://eudml.org/doc/39130
ER -

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