87   Artículos

 
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
João N. Ribeiro da Silva, Tiago A. Santos and Angelo P. Teixeira    
This paper develops a methodology to estimate ship emissions using Automatic Identification System data (AIS). The methodology includes methods for AIS message decoding and ship emission estimation based on the ship?s technical and operational characteri... 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
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
Pedro Pintor, Manuel Lopez-Martinez, Emilio Gonzalez, Jan Safar and Ronan Boyle    
Global Navigation Satellite System (GNSS) technology supports all phases of maritime navigation and serves as an integral component of the Automatic Identification System (AIS) and, by extension, Vessel Traffic Service (VTS) systems. However, the accurac... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Miro Petkovic, Igor Vujovic, Zvonimir Lu?ic and Jo?ko ?oda    
Automated surveillance systems based on machine learning and computer vision constantly evolve to improve shipping and assist port authorities. The data obtained can be used for port and port property surveillance, traffic density analysis, maritime safe... ver más
Revista: Journal of Marine Science and Engineering    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
Hyowon Ban and Hye-jin Kim    
This research is a pilot study to develop a maritime traffic control system that supports the decision-making process of control officers, and to evaluate the usability of a prototype tool developed in this study. The study analyzed the movements of mult... ver más
Revista: ISPRS International Journal of Geo-Information    Formato: Electrónico

 
en línea
Jeong-Hyun Yoon, Dong-Ham Kim, Sang-Woong Yun, Hye-Jin Kim and Sewon Kim    
Container terminals are at the center of global logistics, and are highly dependent on the schedule of vessels arriving. Conventional ETA records from ships, utilized for terminal berth planning, lack sufficient accuracy for effective plan implementation... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Yihan Niu, Feixiang Zhu, Moxuan Wei, Yifan Du and Pengyu Zhai    
Maritime Autonomous Surface Ships (MASS) are becoming of interest to the maritime sector and are also on the agenda of the International Maritime Organization (IMO). With the boom in global maritime traffic, the number of ships is increasing rapidly. The... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

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