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On the Limits of Univariate Deep Learning for Significant Wave Height Forecasting

Zhai, Yilin et al.
arXiv (All) · Papers
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atmospheric-and-oceanic-physicscomputational-physicsmachine-learning
This study conducts a systematic hyperparameter search across five deep learning architectures, DLinear, LSTM, PatchTST, ResAttLstm, and Mamba2, and nine context lengths (1-168 h) for single-station significant wave height (Hs) forecasting on NDBC buoy 41009, followed by re-evaluation of the best co
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