风险评估
多元统计
风险管理
风险分析(工程)
贝叶斯概率
计算机科学
运筹学
精算学
工程类
业务
人工智能
计算机安全
机器学习
财务
作者
Jason R. W. Merrick,Rene Van Dorp
出处
期刊:Risk Analysis
[Wiley]
日期:2005-12-23
卷期号:26 (1): 223-237
被引量:90
标识
DOI:10.1111/j.1539-6924.2006.00708.x
摘要
Several major risk studies have been performed in recent years in the maritime transportation domain. These studies have had significant impact on management practices in the industry. The first, the Prince William Sound risk assessment, was reviewed by the National Research Council and found to be promising but incomplete, as the uncertainty in its results was not assessed. The difficulty in assessing this uncertainty is the different techniques that need to be used to model risk in this dynamic and data-scarce application area. In previous articles, we have developed the two pieces of methodology necessary to assess uncertainty in maritime risk assessment, a Bayesian simulation of the occurrence of situations with accident potential and a Bayesian multivariate regression analysis of the relationship between factors describing these situations and expert judgments of accident risk. In this article, we combine the methods to perform a full-scale assessment of risk and uncertainty for two case studies. The first is an assessment of the effects of proposed ferry service expansions in San Francisco Bay. The second is an assessment of risk for the Washington State Ferries, the largest ferry system in the United States.
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