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Yang, Y., Cui, Z., Wu, J., et al. (2012) Trajectory Analysis Using Spectral Clustering and Sequence Pattern Mining. Journal of Computational Information Systems, 8, 2637-2645.

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  • 标题: 基于AIS数据的船舶异常行为检测方法Abnormal Vessel Behavior Detection Based on AIS Data

    作者: 张树波, 唐强荣

    关键字: AIS数据, 异常行为, 船舶航迹, 行为建模, 异常检测AIS Data, Abnormal Behavior, Vessel Trajectory, Behavioral Modeling, Anomaly Detection

    期刊名称: 《Artificial Intelligence and Robotics Research》, Vol.4 No.4, 2015-11-09

    摘要: 船舶行为检测是海事监控和管理的重要内容,它对于船舶安全航行、港口正常作业生产、海洋环境保护和防止各种水上非法活动具有重要意义。随着越来越多的船舶安装了AIS系统,大量AIS数据的积累为研究船舶运动规律和进行船舶异常行为检测提供了新的途径。本文对近年来AIS数据在船舶异常行为检测方面的研究进展和所取得的成果进行总结和评述,分析了现有方法存在的问题和面临的挑战,指出了AIS数据在船舶异常行为检测方面的主要研究方向。 Maritime behavior detection is critical for maritime surveillance and management. It is important for ship’s safe sailing, normal production at ports, marine environmental protection, water illegal activities prevention and so on. With more and more AIS systems are installed on board, massive amounts of AIS data have been accumulated, which provides us with promising ways to investigate the law of ship motions and the detection of abnormal behaviours. In this paper, various algorithms used for detecting abnormal behaviours of ship are reviewed and commented, and the challenge of researchers in this field faced is then pointed out, in the end, the perspectives in this realm are also proposed.