Enabling a Powerful Marine and Offshore Decision‐Support Solution Through Bayesian Network Technique
Enabling a Powerful Marine and Offshore Decision‐Support Solution Through Bayesian Network Technique
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DOI：
10.1111/j.1539-6924.2006.00775.x
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发表时间：
2006-06
期刊：
影响因子：
3.8
通讯作者：
A. G. Eleye-Datubo;A. Wall;A. Saajedi;Jin Wang
中科院分区：
文献类型：
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作者：
A. G. Eleye-Datubo;A. Wall;A. Saajedi;Jin Wang
在任何对安全至关重要的船舶或海上装置及其系统面临不确定性的情况下做决策时，一个强有力的实用解决方案无疑是最理想的结果。由于数据和信息通常是逐步获取的，贝叶斯网络（BN）被证明能够切实处理随机不确定性，同时使风险评估更易于构建和检验。提出了一种匹配良好的方法来规范推理过程，其中推理处理的核心机制依赖于合理的贝叶斯规则/定理，从而使逻辑成立。通过决策节点和效用节点扩展一个或多个影响节点参数也会产生一个影响图（ID）。通过一个商业计算机工具开发的船舶疏散场景以及授权船舶与浮式生产储油卸油装置碰撞场景展示了贝叶斯网络和影响图的可行性。还介绍了对所产生结果的敏感性分析和验证。
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.