Very short-term prediction of ship motion is critically important in many scenarios such as carrier aircraft landings and marine engineering *** paper introduces the newly developed functional deep learning model,name...
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Very short-term prediction of ship motion is critically important in many scenarios such as carrier aircraft landings and marine engineering *** paper introduces the newly developed functional deep learning model,named as Deep Operator networks neural network(DeepOnet)to predict very short-term ship motion in *** takes wave height as input and predicts ship motion as output,employing a cause-to-effect prediction *** modeling data for this study is derived from publicly available experimental data at the Iowa Institute of Hydraulic ***,the tuning of the hyperparameters within the neural network system was conducted to identify the optimal parameter ***,the DeepOnet model for wave height and multi-degree-of-freedom motion was established,and the impact of increasing time steps on prediction accuracy was ***,a comparative analysis was performed between the DeepOnet model and the classical time series model,long short-term memory(LSTM).It was observed that the DeepOnet model exhibited a tenfold improvement in accuracy for roll and heave ***,as the forecast duration increased,the advantage of the DeepOnet model showed a trend of *** a functional prediction model,DeepOnet offers a novel and promising tool for very short-term ship motion prediction.
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