Multi-scale adaptive decomposition for electricity load forecasting: A deep learning framework for smart-grid applications
An adaptive multi-scale decomposition framework comprising three modules, which offers a competitive accuracy-efficiency trade-off for electricity-load benchmark forecasting under mixed or shifting temporal periodicities, and its applicability to real-world smart-grid operations requires further validation.