Ground-Based GNSS Atmospheric Remote Sensing for Ultra-Short-Term Wind-Power Forecasting: A Direction-Proxy-Guided Graph-Residual Approach
The proposed model combining a long short-term memory backbone, GNSS conditioning, and a graph neural network (GNN), denoted LSTM+GNN+GNSS, for 4 h wind-power forecasting demonstrates the incremental predictive value of the complete GNSS-conditioning pathway under the chronological holdout protocol.
Pei-Yan Gong, Chao-Xia Yuan
· Remote Sensing · 0 citations