@article{ref1,
title="A flexible hierarchical Bayesian modeling technique for risk analysis of major accidents",
journal="Risk analysis",
year="2017",
author="Yu, Hongyang and Khan, Faisal and Veitch, Brian",
volume="37",
number="9",
pages="1668-1682",
abstract="Safety analysis of rare events with potentially catastrophic consequences is challenged by data scarcity and uncertainty. Traditional causation-based approaches, such as fault tree and event tree (used to model rare event), suffer from a number of weaknesses. These include the static structure of the event causation, lack of event occurrence data, and need for reliable prior information. In this study, a new hierarchical Bayesian modeling based technique is proposed to overcome these drawbacks. The proposed technique can be used as a flexible technique for risk analysis of major accidents. It enables both forward and backward analysis in quantitative reasoning and the treatment of interdependence among the model parameters. Source-to-source variability in data sources is also taken into account through a robust probabilistic safety analysis. The applicability of the proposed technique has been demonstrated through a case study in marine and offshore industry.<br><br>© 2017 Society for Risk Analysis.<p /> <p>Language: en</p>",
language="en",
issn="0272-4332",
doi="10.1111/risa.12736",
url="http://dx.doi.org/10.1111/risa.12736"
}