Statistical analysis of the different operator involved in the fuzzy inference process

  • Authors:

  • O. Valenzuela;I. Rojas;F. Rojas

  • Affiliations:

  • Department of Mathematics, University of Granada, Granada, Spain;Department of Computer Architecture and Computer Technology, University of Granada, Granada, Spain;Department of Computer Architecture and Computer Technology, University of Granada, Granada, Spain

  • Venue:
  • WILF'03 Proceedings of the 5th international conference on Fuzzy Logic and Applications
  • Year:
  • 2003

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Abstract

The main architectures, learning abilities and applications of fuzzy systems are well documented. However, to the best of our knowledge, no in-depth analyses have been carried out into the influence on the behaviour of the fuzzy system arising from the use of different alternatives for the design of the fuzzy inference process (mainly, different implication operators and T-norm). Thus, as a complement to the existing intuitive knowledge, it is necessary to have a more precise understanding of the significance of the different alternatives. In the present contribution, the relevance and relative importance of the parameters involved in such a design are investigated by using a statistical tool, the ANalysis Of the VAriance (ANOVA).