A residual-learning hybrid model improves wind turbine power prediction by 37% MAPE over a physics-based model and provides SHAP-based explanations and conformal prediction intervals.
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Integrating Physics and Data-Driven Approaches: An Explainable and Uncertainty-Aware Hybrid Model for Wind Turbine Power Prediction
A residual-learning hybrid model improves wind turbine power prediction by 37% MAPE over a physics-based model and provides SHAP-based explanations and conformal prediction intervals.