Perception based hybrid intelligent systems in petroleum applications

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

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

2 Citas (Scopus)

Resumen

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.

Idioma originalInglés
Título de la publicación alojadaAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS
Páginas649-654
Número de páginas6
DOI
EstadoPublicada - 2006
Publicado de forma externa
EventoNAFIPS 2006 - 2006 Annual Meeting of the North American Fuzzy Information Processing Society - Montreal, QC, Canadá
Duración: 3 jun. 20066 jun. 2006

Serie de la publicación

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

Conferencia

ConferenciaNAFIPS 2006 - 2006 Annual Meeting of the North American Fuzzy Information Processing Society
País/TerritorioCanadá
CiudadMontreal, QC
Período3/06/066/06/06

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