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Proceedings Paper

Coupled Probabilistic And Possibilistic Uncertainty Estimation In Rule-Based Analysis Systems
Author(s): L. Tsoukalas; M. Ragheb
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Paper 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.

Paper Details

Date Published: 11 May 1987
PDF: 9 pages
Proc. SPIE 0786, Applications of Artificial Intelligence V, (11 May 1987); doi: 10.1117/12.940605
Show Author Affiliations
L. Tsoukalas, The University of Illinois at Urbana-Champaign (United States)
M. Ragheb, The University of Illinois at Urbana-Champaign (United States)

Published in SPIE Proceedings Vol. 0786:
Applications of Artificial Intelligence V
John F. Gilmore, Editor(s)

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