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Monte Carlo Sampling for Generalized Knowledge Dependence with Application to Human Reliability
Author(s) -
Cooke Roger M.,
Waij Rudi
Publication year - 1986
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/j.1539-6924.1986.tb00226.x
Subject(s) - monte carlo method , reliability (semiconductor) , independence (probability theory) , computer science , sampling (signal processing) , monte carlo method in statistical physics , monte carlo molecular modeling , importance sampling , statistical physics , hybrid monte carlo , reliability engineering , statistics , mathematics , engineering , markov chain monte carlo , physics , power (physics) , filter (signal processing) , quantum mechanics , computer vision
A general discussion of knowledge dependence in risk calculations shows that the assumption of independence underlying standard Monte Carlo simulation in uncertainty analysis is frequently violated. A model is presented for performing Monte Carlo simulation when the variabilities of the component failure probabilities are either negatively or positively coupled. The model is applied to examples in human reliability analysis and the results are compared to the results of Sandia Laboratories as published in the Peer Review Study and to recalculations using more recent methods of uncertainty analysis.