DocumentCode
845899
Title
Comments on the benchmarks in "A proposal for improving the accuracy of Linguistic Modeling" and related articles
Author
Roubos, J.A. ; Babuska, Robert
Author_Institution
Delft Center for Syst. & Control, Delft Univ. of Technol., Netherlands
Volume
11
Issue
6
fYear
2003
Firstpage
861
Lastpage
865
Abstract
In the above paper by Cordon and Herrara (IEEE Trans. Fuzzy Syst., vol. 8, p. 335-44, 2000), the so-called accurate linguistic modeling (ALM) method was proposed to improve the accuracy of linguistic fuzzy models. A number of examples are given to demonstrate the benefits of the approach. We show that: 1) these examples are not suitable as benchmarks or demonstrators of nonlinear modeling techniques and 2) better results can be obtained by using both standard regression tools as well as other fuzzy modeling techniques. We argue that benchmark examples that are used in articles to demonstrate the effectiveness of fuzzy modeling techniques should be selected with great care. Critical analysis of the results should be made and linear models should be regarded as a lower bound on the acceptable performance.
Keywords
fuzzy logic; learning (artificial intelligence); modelling; pattern clustering; polynomials; regression analysis; splines (mathematics); Takagi-Sugeno fuzzy model; accurate linguistic modeling method; benchmarks; demonstrators; fuzzy modeling techniques; linear models; linguistic fuzzy models; nonlinear modeling techniques; rice data problem; spline model; standard regression tools; Accuracy; Data analysis; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Linear regression; Neural networks; Performance analysis; Proposals; Spline;
fLanguage
English
Journal_Title
Fuzzy Systems, IEEE Transactions on
Publisher
ieee
ISSN
1063-6706
Type
jour
DOI
10.1109/TFUZZ.2003.819822
Filename
1255421
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