Multi-direction prediction based on SALSTM model for ship motion

Shunda Xun; Pengcheng Zhu; Binghua Yang; Jin Xiong

doi:10.1117/12.2690178

10 August 2023 Multi-direction prediction based on SALSTM model for ship motion

Shunda Xun, Pengcheng Zhu, Binghua Yang, Jin Xiong

Proceedings Volume 12748, 5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023); 127483F (2023) https://doi.org/10.1117/12.2690178
Event: 5th International Conference on Information Science, Electrical and Automation Engineering (ISEAE 2023), 2023, Wuhan, China

Abstract

This paper proposes a self-attention LSTM (SALSTM) model for ship motion prediction, which combines the advantages of LSTM and self-attention mechanisms. The model also introduces the concept of attention gate. The paper studies the influence of forecast lead time on the prediction accuracy of three degrees of freedom: roll, surge and heave. The paper compares the SALSTM model with a baseline LSTM model on a ship motion data set under different forecast durations and lead times. The paper evaluates the performance of the SALSTM model using four metrics and verifies its effectiveness under three representative working conditions. The paper also gives the applicable conditions of the SALSTM model for ship motion prediction

Citation Download Citation

Shunda Xun, Pengcheng Zhu, Binghua Yang, and Jin Xiong "Multi-direction prediction based on SALSTM model for ship motion", Proc. SPIE 12748, 5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023), 127483F (10 August 2023); https://doi.org/10.1117/12.2690178

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