A Bayesian Network-Based Approach to Port State Control Ship Detention Risk Assessment
A Bayesian Network-Based Approach to Port State Control Ship Detention Risk Assessment
Building a ship detention risk model can help Port State Control Official(PSCO)to accurately select ships with higher detention risk and improve the efficiency of port state supervision.This paper uses data from a total of 1893 ship inspection reports in the Data Paris MoU database to construct a model using Bayesian Network(BN),and uses sensitivity methods to analyze the relationship between the influence of inherent ship attributes,PSC inspection items,the number of ship defects and ship detention.The results show that pollution prevention,navigation safety equipment and the number of defects are the key inspection items affecting ship detention,and when the ship has the above defects,the ship detention rate increases to 12.85%,11.07%and 22.19%respectively.Therefore,the key inspection items can be prioritized to determine the ship condition,quantitatively analyze the ship detention risk and provide suggestions for port state authorities to make ship detention decisions.
Dingheng Yu; Bing Wu; Pei Chen;
School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan, Hubei,430063##Intelligent Transport Systems Research Centre, Wuhan University of Technology, Wuhan, Hubei,430063;Intelligent Transport Systems Research Centre, Wuhan University of Technology, Wuhan, Hubei,430063##National Engineering Research Center for Water Transport Safety (WTSC),Wuhan, Hubei, 430063;Dong jiakou Maritime Safety Administration, Qingdao, Shandong, 266002;
Port State Control Bayesian Networks ship detention sensitivity analysis
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