MCformer: Multivariate Time Series Forecasting with Mixed-Channels Transformer

arXiv:2403.09223v1 Announce Type: new
Abstract: The massive generation of time-series data by largescale Internet of Things (IoT) devices necessitates the exploration of more effective models for multivariate time-series forecasting. In previous models, there was a predominant use of the Channel Dependence (CD) strategy (where each channel represents a univariate sequence). Current state-of-the-art (SOTA) models primarily rely on the Channel Independence (CI) strategy. The CI strategy treats all channels as a single channel, expanding the dataset to improve generalization performance and …

abstract art arxiv channels cs.lg current data devices exploration forecasting internet internet of things iot massive mixed multivariate series state strategy time series time series forecasting transformer type