Comments on the benchmarks in "A proposal for improving the accuracy of Linguistic Modeling" and related articles

  • Authors:
  • J. A. Roubos;R. Babuska

  • Affiliations:
  • Delft Center for Syst. & Control, Delft Univ. of Technol., Netherlands;-

  • Venue:
  • IEEE Transactions on Fuzzy Systems
  • Year:
  • 2003

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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.