Forecast of Significant Wave Height Based on Deep Learning
Wave climate forecasting plays a crucial role in marine-related engineering,with significant wave height being one of the key parameters.In this study,a two-stage deep learning model is constructed,utilizing convolutional neural networks and long short-term memory networks to learn the spatio-temporal relationships between wind and waves in a phased manner,thus achieving a high-precision forecast of significant wave height.
NETL
NSTL
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