Deep Learning for Cross-Border Electricity Price Forecasting: A Comparative Study
A comparative evaluation of six deep learning models--covering state-space, MLP, RNN, and Transformer-based architectures--emphasizing generalization across markets suggests that N-HiTS and NBEATSx perform competitively in limited-data scenarios, while transformer-based models can reach comparable accuracy but tend to require more adaptation and tuning.
H.S.M. Elashhab, Sai Srijan Papineni, M. Dorn et al.
· IEEE Access · 0 citations