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Generating and Tuning the Fuzzy Logic Systems Developed in Transportation Applications

  • Dušan Teodorovič
  • Katarina Vukadinovič
Part of the International Series in Intelligent Technologies book series (ISIT, volume 13)

Abstract

A successful application of fuzzy logic implies prior determination of shapes of membership functions of input and output variables as well as generation of a fuzzy rule base. In some applications, the final set of fuzzy rules and the choice of membership functions are defined by trial and error. Mendel (1995) claims: “Prior to 1992, all fuzzy logic systems reported in the open literature fixed the parameters of the membership functions somewhat arbitrarily, e.g., the locations and spreads of the membership functions were chosen by the designer independent of the numerical training data. Then, at the first IEEE Conference on Fuzzy Systems, held in San Diego, three different groups of researchers presented the same idea: tune the parameters of a fuzzy logic system using the numerical training data.”

Keywords

Membership Function Fuzzy System Fuzzy Rule Fuzzy Logic System Fuzzy Rule Base 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1998

Authors and Affiliations

  • Dušan Teodorovič
    • 1
  • Katarina Vukadinovič
    • 1
  1. 1.Faculty of Transport and Traffic EngineeringUniversity of BelgradeBelgradeYugoslavia

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