TY  - JOUR
PY  - 2017//
TI  - A flexible hierarchical Bayesian modeling technique for risk analysis of major accidents
JO  - Risk analysis
A1  - Yu, Hongyang
A1  - Khan, Faisal
A1  - Veitch, Brian
SP  - 1668
EP  - 1682
VL  - 37
IS  - 9
N2  - 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>
LA  - en
SN  - 0272-4332
UR  - http://dx.doi.org/10.1111/risa.12736
ID  - ref1
ER  -