62   Artículos

 
en línea
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... ver más
Revista: ISPRS International Journal of Geo-Information    Formato: Electrónico

 
en línea
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 ... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Sheng Zhang, Guangzhong Liu and Chen Cheng    
Over the past few decades, unmanned surface vehicles (USV) have drawn a lot of attention. But because of the wind, waves, currents, and other sporadic disturbances, it is challenging to understand and collect correct data about USV dynamics. In this pape... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Zhaojin Yan, Guanghao Yang, Rong He, Hui Yang, Hui Ci and Ran Wang    
Automatic identification systems (AIS) provides massive ship trajectory data for maritime traffic management, route planning, and other research. In order to explore the valuable ship traffic characteristics contained implicitly in massive AIS data, a sh... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Guangdong Han, Jian Li, Yizong Chen, Shenghai Wang and Haiquan Chen    
Ship cargo-hold cleaning is a low-efficiency and high-risk operation in marine industry, which is generally carried out manually, putting the workers in danger. To improve the efficiency and safety of ship cargo-hold cleaning, a C-DCR is proposed in this... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
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... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Chang Liu, Shize Zhang, Lufang Cao and Bin Lin    
Automatic identification system (AIS) data record a ship?s position, speed over ground (SOG), course over ground (COG), and other behavioral attributes at specific time intervals during a ship?s voyage. At present, there are few studies in the literature... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Xinyu Wang and Yingjie Xiao    
The rapid growth of ship traffic leads to traffic congestion, which causes maritime accidents. Accurate ship trajectory prediction can improve the efficiency of navigation and maritime traffic safety. Previous studies have focused on developing a ship tr... ver más
Revista: Information    Formato: Electrónico

 
en línea
Daping Xi, Yuhao Feng, Wenping Jiang, Nai Yang, Xini Hu and Chuyuan Wang    
The extraction of ship behavior patterns from Automatic Identification System (AIS) data and the subsequent prediction of travel routes play crucial roles in mitigating the risk of ship accidents. This study focuses on the Wuhan section of the dendritic ... ver más
Revista: ISPRS International Journal of Geo-Information    Formato: Electrónico

 
en línea
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... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

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