aceMulti-objective optimized signal decomposition with explainable and reliable hybrid models for multistep significant wave height forecasting in ocean wave energy applications
Accurate forecasting of significant wave height (Hs) is vital for marine safety, coastal engineering, and renewable energy production. This study presents an effective integrated model system to forecast Hs for two distinct sites in Australia, Gladstone and Palm Beach, over various time horizons from 30-min to 24-h ahead during the period of 2018 to 2022. In the first stage, a novel multi-objective Optuna is developed to optimize the decomposition parameters using two criteria of compactness, bandwidth, and peak…
Using SHAP to cut 37 to 48 decomposed inputs down to one dominant predictor kept accuracy nearly unchanged and lowered computational cost, supporting wave energy and coastal hazard planning.
The lower bound of R2 (0.49) shows accuracy dropped at some stations or horizons, and reliability above 88% is only reported for forecasts up to 6 hours ahead, with only two sites tested.
Evidence
- Peer-reviewedEngineering Applications of Artificial Intelligence2026-10-14
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Truvace Impact Record TRV-2026-1543, v1: “Multi-objective optimized signal decomposition with explainable and reliable hybrid models for multistep significant wave height forecasting in ocean wave energy applications.” Truvace, 2026-10-16. /record/TRV-2026-1543 (accessed at citation time). sha256 9df9a6126853e8b3…
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