Treffer: Orthogonal-back propagation hybrid learning algorithm for type-2 fuzzy logic systems

Title:
Orthogonal-back propagation hybrid learning algorithm for type-2 fuzzy logic systems
Authors:
MENDEZ, G. M
Source:
NAFIPS 2004 (2004 Annual Meeting of the North American Fuzzy Information Processing Society). :899-902
Publisher Information:
Piscataway NJ: IEEE, 2004.
Publication Year:
2004
Physical Description:
print, 17 ref 2
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Intelligence artificielle, Artificial intelligence, Acier, Steel, Acero, Algorithme apprentissage, Learning algorithm, Algoritmo aprendizaje, Algorithme flou, Fuzzy algorithm, Algoritmo borroso, Algorithme rétropropagation, Backpropagation algorithm, Algoritmo retropropagación, Arithmétique intervalle, Interval arithmetic, Aritmética intervalo, Entrée sortie, Input output, Entrada salida, Estimation paramètre, Parameter estimation, Estimación parámetro, Finissage, Finishing, Acabado, Identification système, System identification, Identificación sistema, Intelligence artificielle, Artificial intelligence, Inteligencia artificial, Logique floue, Fuzzy logic, Lógica difusa, Modélisation, Modeling, Modelización, Méthode moindre carré, Least squares method, Método cuadrado menor, Programmation logique, Logical programming, Programación lógica, Température superficielle, Surface temperature, Temperatura superficial, Théorie type, Type theory
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Departamento de Ingenieria Electromecànica y Electrónica Instituto Tecnológico de Nuevo León Av. Eloy Cavazos #2001, Cd, Guadalupe, NL, CP 67170, Mexico
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=17808697
Rights:
Copyright 2006 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.17808697
Database:
PASCAL Archive

Weitere Informationen

This article presents a new learning methodology based on a hybrid algorithm for interval type-2 fuzzy logic systems (FLS) parameters estimation. Using input-output data pairs during the forward pass of the training process, the type-2 FLS output is calculated and the consequent parameters are estimated by orthogonal least-squares (OLS) method. In the backward pass, the error propagates backward, and the antecedent parameters are estimated by back-propagation (BP) method. The proposed hybrid methodology was used to construct a type-2 fuzzy model capable of approximate the behaviour of the steel strip temperature as it is being rolled in an industrial Hot Strip Mill (HSM) and used to predict the transfer bar surface temperature at finishing Scale Breaker (SB) entry zone. Comparative results show the advantage of the hybrid learning method (OLS-BP) over that with only BP.