SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion

arXiv:2404.14197v1 Announce Type: new
Abstract: Multivariate time series forecasting plays a crucial role in various fields such as finance, traffic management, energy, and healthcare. Recent studies have highlighted the advantages of channel independence to resist distribution drift but neglect channel correlations, limiting further enhancements. Several methods utilize mechanisms like attention or mixer to address this by capturing channel correlations, but they either introduce excessive complexity or rely too heavily on the correlation to achieve satisfactory results under distribution drifts, particularly …

arxiv core cs.lg forecasting fusion multivariate series time series time series forecasting type