Physics and data dual-driven deep learning model for tide level forecasting

Jiange Jiao

doi:10.1016/j.oceaneng.2025.124134

Physics and data dual-driven deep learning model for tide level forecasting

2026-01-02

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DOI：10.1016/j.oceaneng.2025.124134

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• A novel physics-data dual-driven tidal level forecasting model is proposed. • The model is rigorously validated across all tidal types. • In 1∼24h predictions, it achieves significantly higher accuracy. • Validated at 12 U.S./Japan stations, confirming cross-region adaptability. • Bayesian optimization balances physical and data loss to improve model performance.

Physics and data dual-driven deep learning model for tide level forecasting

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