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Title: Top-down versus bottom-up processing of influence diagrams in probabilistic analysis

Abstract

Recent work by Phillips et al., and Selby et al., has shown that influence diagram methodology can be a useful analytical tool in reactor safety studies. An influence diagram is a graphical representation of probabilistic dependence within a system or event sequence. Bayesian statistics are employed to transform the relationships depicted in the influence diagram into the correct expression for a desired marginal probability (e.g. the top event). As with fault trees, top-down and bottom-up algorithms have emerged as the dominant methods for quantifying influence diagrams. Purpose of this paper is to demonstrate a potential error in employing the bottom-up algorithm when dealing with interdependencies. In addition, the computing efficiency of both methods is discussed.

Authors:
; ;
Publication Date:
Research Org.:
Tennessee Univ., Knoxville (USA); Oak Ridge National Lab., TN (USA)
OSTI Identifier:
6079284
Report Number(s):
CONF-841105-53
ON: DE85005381
DOE Contract Number:  
AC05-84OR21400
Resource Type:
Conference
Resource Relation:
Conference: Joint meeting of the American Nuclear Society and the Atomic Industrial Forum, Washington, DC, USA, 11 Nov 1984
Country of Publication:
United States
Language:
English
Subject:
22 GENERAL STUDIES OF NUCLEAR REACTORS; ALGORITHMS; REACTOR SAFETY; STATISTICS; ERRORS; PROBABILITY; MATHEMATICAL LOGIC; MATHEMATICS; SAFETY; 220900* - Nuclear Reactor Technology- Reactor Safety

Citation Formats

Timmerman, R D, Burns, T J, and Dodds, Jr, H L. Top-down versus bottom-up processing of influence diagrams in probabilistic analysis. United States: N. p., 1984. Web.
Timmerman, R D, Burns, T J, & Dodds, Jr, H L. Top-down versus bottom-up processing of influence diagrams in probabilistic analysis. United States.
Timmerman, R D, Burns, T J, and Dodds, Jr, H L. 1984. "Top-down versus bottom-up processing of influence diagrams in probabilistic analysis". United States. https://www.osti.gov/servlets/purl/6079284.
@article{osti_6079284,
title = {Top-down versus bottom-up processing of influence diagrams in probabilistic analysis},
author = {Timmerman, R D and Burns, T J and Dodds, Jr, H L},
abstractNote = {Recent work by Phillips et al., and Selby et al., has shown that influence diagram methodology can be a useful analytical tool in reactor safety studies. An influence diagram is a graphical representation of probabilistic dependence within a system or event sequence. Bayesian statistics are employed to transform the relationships depicted in the influence diagram into the correct expression for a desired marginal probability (e.g. the top event). As with fault trees, top-down and bottom-up algorithms have emerged as the dominant methods for quantifying influence diagrams. Purpose of this paper is to demonstrate a potential error in employing the bottom-up algorithm when dealing with interdependencies. In addition, the computing efficiency of both methods is discussed.},
doi = {},
url = {https://www.osti.gov/biblio/6079284}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Jan 01 00:00:00 EST 1984},
month = {Sun Jan 01 00:00:00 EST 1984}
}

Conference:
Other availability
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