|本期目录/Table of Contents|

[1]张 凡,王育红*.基于贝叶斯网络的船舶港口国监督检查滞留风险研究[J].宁波大学学报(理工版),2020,33(3):111-115.
 ZHANG Fan,WANG Yuhong*.Detain risk of ship’s port state control inspection based on Bayesian networks[J].Journal of Ningbo University(Natural Science & Engineering Edition),2020,33(3):111-115.
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基于贝叶斯网络的船舶港口国监督检查滞留风险研究(PDF)
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《宁波大学学报》(理工版)[ISSN:1001-5132/CN:33-1134/N]

卷:
第33卷
期数:
2020年3期
页码:
111-115
栏目:
出版日期:
2020-05-10

文章信息/Info

Title:
Detain risk of ship’s port state control inspection based on Bayesian networks
作者:
张 凡 王育红*
宁波大学 海运学院, 浙江 宁波 315832
Author(s):
ZHANG Fan WANG Yuhong*
Faculty of Maritime and Transportation, , 315832,
关键词:
滞留风险 贝叶斯网络 港口国监督检查 动态分析
Keywords:
detain risk Bayesian networks port state control inspection dynamic analysis
分类号:
U691+.6
DOI:
-
文献标志码:
A
摘要:
针对港口国监督(Port State Control, PSC)检查的复杂性和不确定性, 基于贝叶斯网络理论构建船舶PSC检查滞留风险分析模型. 以东京备忘录(Tokyo MOU)中2014~2017年船舶PSC检查样本数据为基础, 运用R语言bnlearn包进行贝叶斯网络的结构及参数学习. 同时分别执行贝叶斯网络的正向、逆向推理, 定量表示各风险因素与滞留结果之间的相互作用关系, 找出导致船舶滞留的高风险因素, 实现不确定环境下船舶PSC检查滞留风险的全面动态分析. 实证表明, 模型具有较高的精确度, 可为检查人员的滞留决策及航运公司的安全风险管理提供有效依据.
Abstract:
In view of the complexity and uncertainty of port state control (PSC) inspection, in this paper a dynamic analysis model is constructed for the detain risk of ship’s PSC inspection using the approach of Bayesian networks. Upon the sample data of ship’s PSC inspection in Tokyo MOU from 2014 to 2017, the structure and parameters of Bayesian networks are studied using the bnlearn package of R language. Mean- while, the forward and backward reasoning of Bayesian networks are carried out to quantitatively express the interaction among the risk factors and detention, and the high-risk factors that affect ship’s detention are determined. A comprehensive and dynamic analysis of the detain risk of ship’s PSC inspection under uncertain environment is conducted. The experimental results show that the model has high accuracy and can provide a valid basis for inspectors’ detention decision-making as well as safety risk management of shipping companies.

参考文献/References:

[1] Gao Z, Lu G, Liu M, et al. A novel risk assessment system for port state control inspection[C]//IEEE International Conference on Intelligence & Security Informatics. IEEE, 2008.
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备注/Memo

备注/Memo:
收稿日期:2019-10-17.宁波大学学报(理工版)网址:http://journallg.nbu.edu.cn/
基金项目:浙江省“钱江人才计划”D类资助项目(QJD1802022);宁波大学王宽诚幸福基金.
第一作者:张凡(1992-),女,江苏宿迁人,在读硕士研究生,主要研究方向:航运风险.Email:zhangfani9@163.com
*通信作者:王育红(1979-),男,英国籍,博士/教授,主要研究方向:综合交通运输.Email:wangyuhong@nbu.edu.cn
更新日期/Last Update: 2020-05-06