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Abnormal Vessel Trajectories Detection in a Port Area Based on AIS Data

机译：基于AIS数据的港口区域船舶航迹异常检测

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摘要

Vessel trajectories anomaly detection in port areas is concerned with finding deviations from normalcy and it is an increasingly important topic when providing decision support for maritime safety administrations. This study proposes an idea that anomalously behaving vessels can be automatically identified from a large Automatic Identification System (AIS) history data by trajectory anomaly detection algorithm. Firstly, the availability of AIS data with a focus on vessel trajectory detection is analyzed in this study. Second, the framework based data mining for vessel trajectory anomaly detection is proposed. Finally, the trajectory anomaly detection algorithm is adopted in order to find the anomalously behaving vessels. Computer programs for decoding, visualization and detection of AIS data have been developed. Experimental results demonstrate that trajectory anomaly detection algorithm in this paper is able to correctly and effectively detect abnormal trajectories from real vessel trajectory data. Research achievements can be applied to intelligent maritime supervision.
机译：在港口区域的船只轨迹异常检测与发现偏离正常状态有关，在为海上安全管理部门提供决策支持时，它已成为越来越重要的话题。这项研究提出了一种想法，即可以通过轨迹异常检测算法从大型自动识别系统（AIS）历史数据中自动识别异常行为的船舶。首先，本研究分析了以船舶航迹检测为重点的AIS数据的可用性。其次，提出了基于框架的船舶轨迹异常检测数据挖掘方法。最后，采用轨迹异常检测算法来发现异常行为的船舶。已经开发了用于解码，可视化和检测AIS数据的计算机程序。实验结果表明，本文的轨迹异常检测算法能够正确，有效地从真实的航迹数据中检测出异常轨迹。研究成果可应用于智能海事监督。

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