2024
DOI: 10.1371/journal.pone.0310385
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Deep learning innovations in South Korean maritime navigation: Enhancing vessel trajectories prediction with AIS data

Umar Zaman,
Junaid Khan,
Eunkyu Lee
et al.

Abstract: Predicting ship trajectories can effectively forecast navigation trends and enable the orderly management of ships, which holds immense significance for maritime traffic safety. This paper introduces a novel ship trajectory prediction method utilizing Convolutional Neural Network (CNN), Deep Neural Network (DNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). Our research comprises two main parts: the first involves preprocessing the large raw AIS dataset to extract features, and the second foc… Show more

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