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Author Makrehchi, M. ♦ Kamel, M.
Sponsorship IEEE Syst., Man & Cybernetics Soc
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2003
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Fuzzy systems ♦ Histograms ♦ Entropy ♦ Genetic algorithms ♦ Mutual information ♦ Marine vehicles ♦ Machine intelligence ♦ System analysis and design ♦ Data engineering ♦ Design engineering
Abstract In this paper, we propose a framework for using real data to generate fuzzy membership functions which is one of the most challenging issues in the design of fuzzy systems. After modelling fuzzy membership functions by fuzzy partitions, an optimization technique based on a genetic algorithm is presented to find near optimal fuzzy partitions. The fitness function of the genetic algorithm is defined using Shannon entropy and mutual information measures to establish a mapping front real data to fuzzy variables. To generate fuzzy membership functions based on fuzzy partitions, some definitions and assumptions are also introduced. Numerical results are provided to demonstrate the effectiveness of the proposed approach.
Description Author affiliation: Dept. of Syst. Design Eng., Waterloo Univ., Ont., Canada (Makrehchi, M.; Kamel, M.)
ISBN 0780379187
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2003-07-24
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 493.45 kB
Page Count 6
Starting Page 44
Ending Page 49


Source: IEEE Xplore Digital Library