Open access
Sep 2026
Short-Term Wind Power Forecasting Based on Sigmoid-Weighted Soft-Switching Strategy Between XGBoost and BP Neural Networks
This paper proposes a hybrid forecasting model with a sigmoid-weighted soft-switching strategy between Extreme Gradient Boosting (XGBoost) and Back Propagation (BP) neural networks, maintaining a lightweight structure and providing an empirical interval for descriptive error-dispersion analysis.
Ye Yin, Han-Tao Wang, Hui Zhang et al.
· Atmosphere · 0 citations