文献类型：期刊文献

中文题名：基于单向距离的谱聚类船舶运动模式辨识

英文题名：Vessel Motion Pattern Recognition Based on One-Way Distance Spectral Clustering Algorithm

作者：马文耀[1,2];吴兆麟[1];杨家轩[1];李伟峰[1]

机构：[1]大连海事大学航海学院;[2]广东海洋大学航海学院

年份：2015

卷号：34

期号：5

起止页码：130

中文期刊名：重庆交通大学学报：自然科学版

收录：CSTPCD、、北大核心2014、北大核心

基金：国家自然科学基金项目(61073134);中央高校基本科研业务费项目(3132013015)

语种：中文

中文关键词：交通运输工程;运动模式;单向距离;谱聚类;相似性度量

外文关键词：transportation engineering; motion pattern; one-way distance; spectral clustering; similarity measure;

中文摘要：利用海事大数据辨识船舶运动模式,能够发现高级别情景意识,提高海事监管技术的效率。提出了一种基于单向距离的谱聚类船舶运动模式辨识方法,充分利用单向距离抗干扰特点,构建了基于单向距离的轨迹相似性度量,得到了轨迹相似度矩阵;以无监督学习方式采用谱聚类算法学习轨迹的空间分布,获取船舶的正常运动模式;以琼州海峡实测AIS数据为样本,研究了进入海口秀英港的船舶运动模式,并分别统计了各模式内及模式之间的距离,获取的4种船舶运动模式与实际相符。实验结果表明:该方法聚类精度高,可以适用于沿海港口、狭水道和船舶交通复杂的区域的船舶运动模式辨识。

外文摘要：The vessel motion pattern recognition from marine large data can discovery high-level situational awareness,which improves the efficiency of maritime surveillance technology. Therefore,a motion pattern of vessel recognition methods based on one-way distance spectral clustering algorithm was proposed. The anti-interference of the one-way distance measurement was fully used to form the similarity value of trajectory based on one-way distance,and then the similarity matrix of the trajectory was also obtained. The regular motion patterns of vessels were extracted from the trajectories spatial distribution learnt by the spectral clustering algorithm in unsupervised learning way. Finally,the motion patterns for vessels entering into Xiuying port were analyzed by using real AIS data sample in Qiongzhou strait. And distance of inner pattern class and distance between of pattern class were calculated separately. Four obtained typical patterns were in consistence with those of the real traffic. The experiment results demonstrate that the proposed clustering methods is of good performance and well fit for identifying motion patterns of vessel in areas,such as coastal ports,narrow channels and complicated traffic zones.