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

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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.

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Sheremetov, L., Batyrshin, I., Filatov, D., Martínez-Muñoz, J. (2006). An Uncertainty Model for a Diagnostic Expert System Based on Fuzzy Algebras of Strict Monotonic Operations. In: Gelbukh, A., Reyes-Garcia, C.A. (eds) MICAI 2006: Advances in Artificial Intelligence. MICAI 2006. Lecture Notes in Computer Science(), vol 4293. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11925231_16

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  • DOI: https://doi.org/10.1007/11925231_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-49026-5

  • Online ISBN: 978-3-540-49058-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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