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基于AIS数据的船舶领域影响因素分析
引用本文:周丹,郑中义.基于AIS数据的船舶领域影响因素分析[J].上海海事大学学报,2016,37(2):7-11.
作者姓名:周丹  郑中义
作者单位:大连海事大学 航海学院,大连海事大学 航海学院
基金项目:国家自然科学基金(51409033)
摘    要:为比较互见中开阔水域不同船舶领域影响因素的重要性,应用粗糙集理论的相关算法,对船舶领域影响因素之间的依赖关系进行分析,并进行影响因素约简和影响因素重要度计算.以渤海及黄海北部船舶自动识别系统(Automatic Identification System, AIS)的数据为基础,应用MATLAB编程计算,得到船舶领域影响因素之间的依赖度、相对约简集和影响因素重要度.结果表明:船舶领域影响因素之间存在不同程度的冗余,其中风、浪或流可约简掉;会遇角度、航速、船舶大小、驾驶员级别、船舶密度、船舶类型和能见度的重要度分别为0.279 1, 0.200 8, 0.179 4, 0.212 1, 0.235 9, 0.122 9和0.093 5.该研究表明:在保证对船舶领域影响分辨性不变的前提下,驾驶员可选择较重要因素对船舶领域进行判断,并采取较恰当的避碰行动,保障航行安全;但在特殊的环境下,某些影响因素需要特别考虑.

关 键 词:影响因素    粗糙集理论    属性约简    重要度
收稿时间:2015/8/18 0:00:00
修稿时间:2015/12/1 0:00:00

Analysis of influencing factors of ship domain based on AIS data
Institution:dalian maritime university maritime engineering college and Dalian Maritime University+Navigation College
Abstract:To compare importances of influencing factors in different ship domains in sight of one another in the open sea area, the relevant algorithms of the rough set theory are applied for the study of the dependence between the factors, then for factor reduction and factor importance calculation. Based on the data of Automatic Identification System (AIS) of Bohai Sea and the north of Yellow Sea, the dependence between the factors, the relative reduced sets of the factors and the importance of the factors are obtained by MATLAB. The results indicate that, there exist different redundancies among the factors, where wind, wave and current can be reduced; the importances of encounter angle, ship speed, ship size, driver level, ship density, ship type and visibility are 0.279 1, 0.200 8, 0.179 4, 0.212 1, 0.235 9, 0.122 9 and 0.093 5, respectively. The research shows that, under the premise of ensuring fixed distinguishing ability of influencing factors in ship domains, drivers should select more important factors to decide ship domain, and the more appropriate collision avoidance actions should be taken for the navigation safety. However, some factors have to be considered in specific situations.
Keywords:influencing factor  rough set theory  attribute reduction  importance
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