ST-Seq2Seq: A Spatio-Temporal Feature-Optimized Seq2Seq Model for Short-Term Vessel Trajectory Prediction

ST-Seq2Seq: A Spatio-Temporal Feature-Optimized Seq2Seq Model for Short-Term Vessel Trajectory Prediction

Deep learning provides appropriate mechanisms to predict vessel trajectories for safer and efficient shipping, but still existing models are mainly oriented to longer-term prediction trends and do not fully support real time navigation needs. While most recent works have been largely exploiting Auto...

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Bibliographic Details
Main Authors: Lan You, Siyu Xiao, Qingxi Peng, Christophe Claramunt, Xuewei Han, Zhengyi Guan, Jiahe Zhang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Sequence-to-sequence (Seq2Seq)
recurrent neural network
spatio-temporal
AIS
vessel trajectory prediction
Online Access:https://ieeexplore.ieee.org/document/9276488/

Internet

https://ieeexplore.ieee.org/document/9276488/

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