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Dapeng Jiang, Guoyou Shi, Na Li, Lin Ma, Weifeng Li and Jiahui Shi
In the context of the rapid development of deep learning theory, predicting future motion states based on time series sequence data of ship trajectories can significantly improve the safety of the traffic environment. Considering the spatiotemporal corre...
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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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Diju Gao, Peng Zhou, Weifeng Shi, Tianzhen Wang and Yide Wang
A new method is proposed for the dynamic obstacle avoidance problem of unmanned surface vehicles (USVs) under the international regulations for preventing collisions at sea (COLREGs), which applies the particle swarm optimization algorithm (PSO) to the d...
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Weifeng Li, Lufeng Zhong, Yang Xu and Guoyou Shi
The traditional ship collision risk index model based on the distance at the closest point of approach (DCPA) and the time to the closest point of approach (TCPA) is insufficient for estimating ship collision risk and planning collision avoidance operati...
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Xing Jiang, Ming Zhong, Jiahui Shi, Weifeng Li, Yi Sui and Yuzhi Dou
As maritime transportation develops, the pressure of port traffic increases. To improve the management of ports and the efficiency of their operations, vessel scheduling must be optimized. The vessel scheduling problem can be divided into channel schedul...
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Bernardo Cockburn, Weifeng Qiu and Ke Shi.
Pág. 1327 - 1353
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Weifeng Feng, Frank G. Shi, Yongzhi He, and Bin Zhao
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Weifeng Feng and Frank G. Shi
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