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August 11, 2025Computational Intelligence

Ship Trajectory Prediction Method Based on Multi‐Layer Recurrent Neural Network Structure and AIS Data Driven

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Authors

JLJunjie LiXihua UniversityXWXiang WangChongqing Jiaotong UniversityJCJing ChenNorth China University of Science and Technology

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Implication

This method enhances trajectory prediction accuracy in vessels, highlighting advancements in navigation and collision avoidance systems.

Key Points

  • Achieving an average of 96.8% and 86.5% accuracy increases in short-term and mid-term predictions, respectively, is noteworthy.
  • The proposed FRA-LSTM method effectively utilizes an attention mechanism within the forward and reverse networks.
  • Dedicated testing demonstrates the system's significant advantages compared with BiLSTM and Seq2Seq models.
  • Successful predictions show promise for future advancements in intelligent maritime navigation and safety.

Cite This Study

Li et al. (2025) studied this question.

synapsesocial.com/papers/68a360d60a429f7973328f59https://doi.org/10.1111/coin.70079
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