RISK ASSESSMENT OF NAUTICAL NAVIGATIONAL ENVIRONMENT BASED ON GREY FIXED WEIGHT CLUSTER

被引:9
作者
Tian, Yanfei [1 ,2 ]
Sun, Xuecheng [3 ]
Chen, Lijia [1 ,2 ]
Huang, Liwen [1 ,2 ]
机构
[1] Wuhan Univ Technol, Sch Nav, 1178 Heping Ave, Wuhan 430063, Hubei, Peoples R China
[2] Hubei Key Lab Inland Shipping Technol, 1178 Heping Ave, Wuhan 430063, Hubei, Peoples R China
[3] Guangzhou Marine Safety Adm, Nansha Dept, 620 Port Ave, Guangzhou 511458, Guangdong, Peoples R China
来源
PROMET-TRAFFIC & TRANSPORTATION | 2017年 / 29卷 / 03期
基金
中国国家自然科学基金;
关键词
nautical navigational environment; risk evaluation; grey fixed weight cluster; fuzzy analytic hierarchy process; fuzzy statistic; QIONGZHOU STRAIT; PERFORMANCE; SYSTEM; CHINA;
D O I
10.7307/ptt.v29i3.2238
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
In order to set up a mathematical model suitable for nautical navigational environment risk evaluation and systematically master the navigational environment risk characteristics of the Qiongzhou Strait in a quantitative way, a risk assessment model with approach steps is set up based on the grey fixed weight cluster (GFWC). The evaluation index system is structured scientifically through both literature review and expert investigation. The relative weight of each index is designed to be obtained via fuzzy analytic hierarchy process (FAHP); Index membership degree of every grey class is proposed to be achieved by fuzzy statistics (FS) to avoid the difficulty of building whiten weight functions. By using the model, nautical navigational environment risk of the Qiongzhou Strait is determined at a "moderate" level according to the principle of maximum membership degree. The comprehensive risk evaluation of the Qiongzhou Strait nautical navigational environment can provide theoretical reference for implementing targeted risk control measures. It shows that the constructed GFWC risk assessment model as well as the presented steps are workable in case of incomplete information. The proposed strategy can excavate the collected experts' knowledge mathematically, quantify the weight of each index and risk level, and finally lead to a comprehensive risk evaluation result. Besides, the adoptions of probability and statistic theory, fuzzy theory, aiming at solving the bottlenecks in case of uncertainty, will give the model a better adaptability and executability.
引用
收藏
页码:331 / 342
页数:12
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