Enabling a powerful marine and offshore decision-support solution through Bayesian network technique.
A powerful practical solution is by far the most desired output when making decisions under the realm of uncertainty on any safety-critical marine or offshore units and their systems. With data and information typically being obtained incrementally, adopting Bayesian network (BN) is shown to realistically deal with the random uncertainties while at the same time making risk assessments easier to build and to check. A well-matched methodology is proposed to formalize the reasoning in which the focal mechanism of inference processing relies on the sound Bayes's rule/theorem that permits the logic. Expanding one or more influencing nodal parameters with decision and utility node(s) also yields an influence diagram (ID). BN and ID feasibility is shown in a marine evacuation scenario and that of authorized vessels to floating, production, storage, and offloading collision, developed via a commercial computer tool. Sensitivity analysis and validation of the produced results are also presented.
Eleye-Datubo
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AG
Marine, Offshore & Transport Research Group, School of Engineering, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK.
Wall
A
A
Saajedi
A
A
Wang
J
J
D000062:Accidents, Occupational / Q000517:prevention & control*; D001499:Bayes Theorem; D003661:Decision Support Techniques; D006801:Humans; D016013:Likelihood Functions; D015233:Models, Statistical; D011336:Probability; D018635:Rescue Work; D012306:Risk; D018570:Risk Assessment / Q000379:methods*; D012680:Sensitivity and Specificity; D012767:Ships; D012984:Software