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Ye Xiao, Yupeng Hu, Jizhao Liu, Yi Xiao and Qianzhen Liu
Ship trajectory prediction is essential for ensuring safe route planning and to have advanced warning of the dangers at sea. With the development of deep learning, most of the current research has explored advanced prediction methods based on historical ...
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Atefe Sedaghat, Homayoon Arbabkhah, Masood Jafari Kang and Maryam Hamidi
This research introduces an online system for monitoring maritime traffic, aimed at tracking vessels in water routes and predicting their subsequent locations in real time. The proposed framework utilizes an Extract, Transform, and Load (ETL) pipeline to...
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Dimitrios Kaklis, Ioannis Kontopoulos, Iraklis Varlamis, Ioannis Z. Emiris and Takis Varelas
Trajectory data holds pivotal importance in the shipping industry and transcend their significance in various domains, including transportation, health care, tourism, surveillance, and security. In the maritime domain, improved predictions for estimated ...
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Thi-Hong-Hanh Nguyen, Tien-Hung Hou, Hai-An Pham and Chia-Cheng Tsai
Pollution caused by marine oil spills can lead to persistent ecological disasters and severe social and economic damages. Numerical simulations are useful and essential tools for accurate decision making during emergencies and planning response actions. ...
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Mingze Li, Bing Li, Zhigang Qi, Jiashuai Li and Jiawei Wu
Predicting ship trajectories plays a vital role in ensuring navigational safety, preventing collision incidents, and enhancing vessel management efficiency. The integration of advanced machine learning technology for precise trajectory prediction is emer...
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Kristoffer Vinther Olesen, Ahcène Boubekki, Michael C. Kampffmeyer, Robert Jenssen, Anders Nymark Christensen, Sune Hørlück and Line H. Clemmensen
The analysis of maritime traffic patterns for safety and security purposes is increasing in importance and, hence, Vessel Traffic Service operators need efficient and contextualized tools for the detection of abnormal maritime behavior. Current models la...
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Lin Ma, Guoyou Shi, Weifeng Li and Dapeng Jiang
Ship trajectory data can be used in most marine-related research, and most ship trajectory data come from AIS. The large number of ships and the short reporting period of AIS have resulted in a huge amount of ship trajectory data, which has caused a cert...
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Wenbo Zhao, Dezhi Wang, Kai Gao, Jiani Wu and Xinghua Cheng
Approximating the positions of vessels near underwater devices, such as unmanned underwater vehicles and autonomous underwater vehicles, is crucial for many underwater operations. However, long-term monitoring of vessel trajectories is challenging due to...
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Xiang Zhang, Yuchuan Zhou and Lianying Li
Recognizing vessel navigation patterns plays a vital role in understanding maritime traffic behaviors, managing and planning vessel activities, spotting outliers, and predicting traffic. However, the growth in trajectory data and the complexity of mariti...
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Wei Li, Jun Zhang, Fang Wang and Hanyun Zhou
The underactuated unmanned surface vessel (USV) has been identified as a promising solution for future maritime transport. However, the challenges of precise trajectory tracking and obstacle avoidance remain unresolved for USVs. To this end, this paper m...
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