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A robust multi-location evaluation of a machine learning framework for wind power forecasting

Fig 24

Cross-location generalization capacity of ML models obtained from the tabulated results.

Bars represent mean R² (± SD) when models are trained on one location and tested on various sites, emphasizing the provisional transferability of RFR, XGBoost, and SVR variations through environments.

Fig 24

doi: https://doi.org/10.1371/journal.pone.0344971.g024