Methods for building Conditional Probability Tables of Bayesian Belief Networks from limited judgment: An evaluation for Human Reliability Application-Reference-Cited by-同舟云学术

Methods for building Conditional Probability Tables of Bayesian Belief Networks from limited judgment: An evaluation for Human Reliability Application

Published:2016-07 Issue: Volume:151 Page:93-112
ISSN:0951-8320
Container-title:Reliability Engineering & System Safety
language:en
Short-container-title:Reliability Engineering & System Safety

Author:

Mkrtchyan L.,Podofillini L.,Dang V.N.

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Safety, Risk, Reliability and Quality

Reference41 articles.

1. Bayesian Belief Networks for predicting drinking water distribution system pipe breaks;Francis;Reliab Eng Syst Saf,2014

2. On the use of the hybrid causal logic method in offshore risk analysis;Røed;Reliab Eng Syst Saf,2009

3. Hybrid causal methodology and software platform for probabilistic risk assessment and safety monitoring of socio-technical systems;Groth;Reliab Eng Syst Saf,2010

4. Network and decision graphs;Jensen,2007

5. Building Probabilistic Networks: “where do the numbers come from?”;Druzdzel;IEEE Trans Knowl Data Eng,2000

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