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Multiresolution Fuzzy Rule Systems

  • Ricardo Ñanculef
  • Carlos Concha
  • Claudio Moraga
  • Héctor Allende
Part of the Advances in Soft Computing book series (AINSC, volume 33)

Abstract

This paper describes the modelling of fuzzy rule systems using a multiresolution strategy that handles the problem of granularization of the input space by using multiresolution linguistic terms. Models of different resolutions are chained by antecedents because linguistic terms of a level j are obtained by refinements of linguistic terms of a superior level j + 1. The models can also be chained by consequents using aggregation procedures. The family of models are called Multiresolution Fuzzy Rule Systems.

A metasemantics based on linguistic operators is proposed for the interpretation of the refinements as a rule specialization. Interesting models result allowing local refinement of rules that preserve the semantic interpretation.

Keywords

Fuzzy Rule Systems Rules Hierarchies Learning Algorithms Multiresolution Analysis 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Ricardo Ñanculef
    • 1
  • Carlos Concha
    • 1
  • Claudio Moraga
    • 2
  • Héctor Allende
    • 1
  1. 1.Department of InformaticsFederico Santa María UniversityValparaísoChile
  2. 2.Department of Computer ScienceUniversity of DortmundDortmundGermany

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