Multiscale attention-based LSTM for ship motion prediction
T Zhang, XQ Zheng, MX Liu - Ocean Engineering, 2021 - Elsevier
Ship motion prediction is applied to the shipboard stabilized platform to keep the equipment
on the platform stable all the time, which is of great practical significance to the safety and …
on the platform stable all the time, which is of great practical significance to the safety and …
SeaBil: Self-attention-weighted ultrashort-term deep learning prediction of ship maneuvering motion
N Wang, X Kong, B Ren, L Hao, B Han - Ocean Engineering, 2023 - Elsevier
Accurate prediction of motion dynamics fundamentally promotes the autonomy of intelligent
ships, but faces great challenges in modeling mechanism. In this paper, to establish data …
ships, but faces great challenges in modeling mechanism. In this paper, to establish data …
Ship motion attitude prediction model based on IWOA-TCN-Attention
B Zhang, S Wang, L Deng, M Jia, J Xu - Ocean Engineering, 2023 - Elsevier
Aiming at the problem of low prediction accuracy of ship motion with the characteristics of
non-stationary, nonlinear and stochastic, this paper proposes a combined prediction model …
non-stationary, nonlinear and stochastic, this paper proposes a combined prediction model …
[HTML][HTML] Deep learning-based ship speed prediction for intelligent maritime traffic management
Improving maritime operations planning and scheduling can play an important role in
enhancing the sector's performance and competitiveness. In this context, accurate ship …
enhancing the sector's performance and competitiveness. In this context, accurate ship …
Incorporating approximate dynamics into data-driven calibrator: A representative model for ship maneuvering prediction
High-fidelity models capable of accurately predicting ship motion are critical for promoting
innovation and efficiency in the maritime industry. However, creating an advanced model …
innovation and efficiency in the maritime industry. However, creating an advanced model …
On the use of dynamic mode decomposition for time-series forecasting of ships operating in waves
In order to guarantee the safety of payload, crew, and structures, ships must exhibit good
seakee**, maneuverability, and structural-response performance, also when they operate …
seakee**, maneuverability, and structural-response performance, also when they operate …
Data-driven models for vessel motion prediction and the benefits of physics-based information
Abstract Machine learning approaches, onboard measurements, and widely available wave
forecast and hindcast data present an opportunity to develop predictive models for vessel …
forecast and hindcast data present an opportunity to develop predictive models for vessel …
[HTML][HTML] Knowledge transfer strategy for enhancement of ship maneuvering model
The advancement of autonomous vehicles and concerns about ship navigation safety have
resulted in a greater need for ship model quality. However, in situations where there is …
resulted in a greater need for ship model quality. However, in situations where there is …
[HTML][HTML] Data-driven uncertainty and sensitivity analysis for ship motion modeling in offshore operations
To build a compact data-driven ship motion model for offshore operations that require high
control safety, it is necessary to select the most influential parameters and to analyze the …
control safety, it is necessary to select the most influential parameters and to analyze the …
Time-series forecasting for ships maneuvering in waves via recurrent-type neural networks
The prediction capability of recurrent-type neural networks is investigated for real-time short-
term prediction (nowcasting) of ship motions in high sea state. Specifically, the performance …
term prediction (nowcasting) of ship motions in high sea state. Specifically, the performance …