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Author Marquez, A.A. ♦ Marquez, F.A. ♦ Peregrin, A.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2012
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Adaptation models ♦ Accuracy ♦ Pragmatics ♦ Complexity theory ♦ Adaptive systems ♦ Computational modeling ♦ Connectors ♦ High-dimensional regression problems ♦ Linguistic fuzzy modelling ♦ Multi-objective genetic fuzzy systems ♦ Adaptive Inference Systems
Abstract Adaptive connectors as conjunction operators of the inference system is one of the methodologies to improve the accuracy of fuzzy rule based systems by means of local adaptation of the inference process to each rule of the rule base. They are usually implemented through the classic adaptive t-norms, but when dealing with high-dimensional problems (several variables and/or instances) the adaptation of their parameters becomes problematic. In this paper, we propose a new adaptive conjunction connector and an associated multi-objective evolutionary learning algorithm which is more efficient and thus suitable for using adaptive connectors in high dimensional problems. The proposal is compared in an experimental study with the use of a well known efficient adaptive t-norm from the literature as conjunction operator. The results obtained on five regression problems confirm the effectiveness of the presented proposal in terms of efficiency, but also in terms of simplicity and compactness of the obtained models.
Description Author affiliation: Information Technologies Department, University of Huelva, Spain (Marquez, A.A.; Marquez, F.A.; Peregrin, A.)
ISBN 9781467315074
ISSN 10987584
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2012-06-10
Publisher Place Australia
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781467315067
Size (in Bytes) 1.28 MB
Page Count 8
Starting Page 1
Ending Page 8

Source: IEEE Xplore Digital Library