H. Kassem

Deep Learning for Renewable Energy Forecasting and Demand Management: A Comparative Review of Architectures, Performance, and Regional Applications

A comprehensive comparative analysis of the deep learning architectures such as Long Short-Term Memory (LSTM), Gated Recurrent Units (GRU), Convolutional Neural Networks (CNN), Transformer models, and hybrid models based on the benchmark of four widely used renewable energy datasets revealed that the hybrid CNN-LSTM mo...