Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping

ArXi:2305.10721v2 Announce Type: replace Materials and methods: We conduct comprehensive experiments on both simulated and real-world datasets to analyze the components of state-of-the-art models. A theoretical analysis is provided to explain the working mechanisms of affine mapping in periodic signal forecasting. We evaluate the impact of reversible normalization and input horizon extension on model robustness.