Coupled probabilistic and possibilistic uncertainty estimation in rule-based analysis systems

L. Tsoukalas, M. Ragheb

Research output: Contribution to journalArticle

Abstract

A methodology is developed for estimating the Performance of monitored engineering devices. Inferencing and decision-making under uncertainty is considered in Production-Rule Analysis systems where the knowledge about the system is both probabilistic and possibilistic. In this case uncertainty is considered as consisting of two components: Randomness describing the uncertainty of occurrence of an object, and Fuzziness describing the imprecision of the meaning of the object. The concepts of information granularity and of the probability of a fuzzy event are used. Propagation of the coupled Probabilistic and possibilistic uncertainty is carried out over model-based systems using the Rule-Based paradigm. The approach provides a measure of both the performance level and the reliability of a device.

Original languageEnglish (US)
Pages (from-to)79-86
Number of pages8
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume786
DOIs
StatePublished - May 11 1987

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ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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