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An Uncertainty Model for a Diagnostic Expert System Based on Fuzzy Algebras of Strict Monotonic Operations

  • Leonid Sheremetov
  • Ildar Batyrshin
  • Denis Filatov
  • Jorge Martínez-Muñoz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4293)

Abstract

Expert knowledge in most of application domains is uncertain, incomplete and perception-based. For processing such expert knowledge an expert system should be able to represent and manipulate perception-based evaluations of uncertainties of facts and rules, to support multiple-valuedness of variables, and to make conclusions with unknown values of variables. This paper describes an uncertainty model based on two algebras of conjunctive and disjunctive multi-sets used by the inference engine for processing perception-based evaluations of uncertainties. The discussion is illustrated by examples of the expert system, called SMART-Agua, which is aimed to diagnose and give solution to water production problems in petroleum wells.

Keywords

Expert System Inference Engine Inference Procedure Fuzzy Expert System Fuzzy Inference Engine 
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-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Leonid Sheremetov
    • 1
  • Ildar Batyrshin
    • 1
  • Denis Filatov
    • 2
  • Jorge Martínez-Muñoz
    • 1
  1. 1.Mexican Petroleum InstituteMexico D.F.Mexico
  2. 2.Centre for Computing ResearchNational Polytechnic InstituteMexico D.F.Mexico

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