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Encoding Fuzzy Diagnosis Rules as Optimisation Problems

  • Antonio Sala
  • Alicia Esparza
  • Carlos Ariño
  • Jose V. Roig
Part of the Lecture Notes Electrical Engineering book series (LNEE, volume 15)

Abstract

This paper discusses how to encode fuzzy knowledge bases for diagnostic tasks (i.e., list of symptoms produced by each fault, in linguistic terms described by fuzzy sets) as constrained optimisation problems. The proposed setting allows more flexibility than some fuzzy-logic inference rulebases in the specification of the diagnostic rules in a transparent, user-understandable way (in a first approximation, rules map to zeros and ones in a matrix), using widely-known techniques such as linear and quadratic programming.

Keywords

Fault detection and diagnosis fuzzy mathematical programming approximate reasoning optimisation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Antonio Sala
    • 1
  • Alicia Esparza
    • 1
  • Carlos Ariño
    • 1
  • Jose V. Roig
    • 1
  1. 1.Systems Engineering and Control Dept.Univ. Politécnica de Valencia Cno. Vera s/n46022 ValenciaSpain

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