AI RESEARCH
VMDNet: Temporal Leakage-Free Variational Mode Decomposition for Electricity Demand Forecasting
arXiv CS.LG
•
ArXi:2509.15394v3 Announce Type: replace Accurate electricity demand forecasting is challenging due to the strong multi-periodicity of real-world demand series, which makes effective modeling of recurrent temporal patterns crucial. Decomposition techniques make such structure explicit and thereby improve predictive performance. Variational Mode Decomposition (VMD) is a powerful signal-processing method for periodicity-aware decomposition and has seen growing adoption in recent years.