Perception based hybrid intelligent systems in petroleum applications

L. B. Sheremetov, I. Z. Batyrshin, D. M. Filatov

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

We describe the methods of processing of perception based information in hybrid intelligent systems. Several innovative techniques like a multi-set based algebra of qualitative perception-based uncertainties and perception-based data mining form the technological framework of the approach. In the paper, we discuss the algebra of strict monotonie operations and inference procedures based on perception-based evaluations of uncertainty of facts and rules. They are characterized by multi-set-based representation of evaluations of uncertainty and by multi-valued inference of conclusions in expert system rules. The proposed method is implemented in the CAPNET Expert System Shell. We also discuss the method of evaluation of perception-based patterns in time series data bases. The approach is illustrated by examples of diagnostics of excessive water production in petroleum wells combining both methods.

Original languageEnglish
Title of host publicationAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS
Pages649-654
Number of pages6
DOIs
StatePublished - 2006
Externally publishedYes
EventNAFIPS 2006 - 2006 Annual Meeting of the North American Fuzzy Information Processing Society - Montreal, QC, Canada
Duration: 3 Jun 20066 Jun 2006

Publication series

NameAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS

Conference

ConferenceNAFIPS 2006 - 2006 Annual Meeting of the North American Fuzzy Information Processing Society
Country/TerritoryCanada
CityMontreal, QC
Period3/06/066/06/06

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