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Methods for Uncertainty Analysis: A Comparative Survey
Author(s) -
Cox David C.,
Baybutt Paul
Publication year - 1981
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.1539-6924.1981.tb01425.x
Subject(s) - monte carlo method , sensitivity (control systems) , probabilistic logic , probabilistic risk assessment , uncertainty analysis , computer science , sensitivity analysis , differential (mechanical device) , risk assessment , uncertainty quantification , data mining , statistics , mathematics , engineering , machine learning , artificial intelligence , simulation , computer security , electronic engineering , aerospace engineering
This paper presents a survey and comparative evaluation of methods which have been developed for the determination of uncertainties in accident consequences and probabilities, for use in probabilistic risk assessment. The methods considered are: analytic techniques, Monte Carlo simulation, response surface approaches, differential sensitivity techniques, and evaluation of classical statistical confidence bounds. It is concluded that only the response surface and differential sensitivity approaches are sufficiently general and flexible for use as overall methods of uncertainty analysis in probabilistic risk assessment. The other methods considered, however, are very useful in particular problems.