Attention-Enhanced CNN–BiLSTM Framework with Temporal Feature Engineering for Global Horizontal Irradiance Forecasting
The proposed CNN–BiLSTM–Attention framework performed better than conventional benchmark models of machine learning and deep learning, achieving a Root Mean Square Error of 0.088 and Seasonal and atmospheric-condition evaluations also showed consistent performance across different seasonal and atmospheric conditions.