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引用次数: 3
摘要
摘要多年来,船舶事故数据少报问题一直困扰着从事海上安全分析的研究人员。为了提高船舶事故记录的质量,本研究提出了一种新的方法,包括三个步骤来补充少报的海上事故记录。第一步是通过问卷调查的方式调查不同情况下的漏报率。基于调查结果,第二步是建立集群特定随机效应(Cluster-Specific Random Effects, CSRE)模型,估算不同情景下的漏报率。然后,第三步是使用蒙特卡罗模拟技术复制少报的事故记录。模型结果表明,液货船漏报事故记录的概率低于其他船舶类别,而渔船漏报的概率更高。非严重事故比严重事故更容易被漏报。案例研究证实了拟议的三步法在补充存在漏报问题的海上事故数据库方面的有效性。
A three-step methodology to complement underreporting maritime accident records
Abstract The underreporting issue on shipping accident data has plagued the researchers focused on maritime safety analysis for many years. For improving the quality of shipping accident records, this study proposes a novel methodology comprising three steps to complement the underreported maritime accident records. The first step is to investigate the underreporting rates under various conditions through questionnaire survey. Based on the survey results, the second step is to build a Cluster-Specific Random Effects (CSRE) model to estimate the underreporting rates under various scenarios. Then, the third step is to replicate the underreported accident records using the Monte Carlo simulation technique. Model results show that the occurrence probability of missing accident records involving liquid cargo ships is lower than other ship categories while fishing ships are more likely to have a higher underreporting rate. Non-serious accidents are more likely to be underreported than serious accidents. The case study confirms the effectiveness of the proposed three-step method for complementing the maritime accident databases suffering underreporting problems.