深度学习在海浪预测中应用研究进展OA北大核心CSTPCD

With advancements in computer technology and observational methods,ocean wave prediction has pro-gressed significantly,particularly through the use of artificial intelligence.Deep learning,a key component of arti-ficial intelligence,has been widely applied to ocean wave prediction.This paper reviews the applications of deep learning models in predicting significant wave heights and wave spectra.It specifically focuses on four areas:sin-gle-point models using time-series preprocessing and long short-term memory(LSTM),ConvLSTM,attention mechanisms,and sequence-to-sequence models for continuous wave height predictions.The review outlines the advantages and disadvantages of deep learning models in ocean wave prediction and proposes solutions to current challenges.Finally,future research regarding wave prediction is summarized.Although deep learning cannot en-tirely replace numerical ocean wave models in theoretical development,they are poised to enhance our understand-ing of spatial and temporal characteristics of ocean waves.This should guide the creation of intelligent big ocean models and the realization of digital twin oceans.