WinNet:time series forecasting with a window-enhanced period extracting and interacting

no code implementations • 1 Nov 2023 • Wenjie Ou, Dongyue Guo, Zheng Zhang, Zhishuo Zhao, Yi Lin

We present a highly accurate and simply structured CNN-based model for long-term time series forecasting tasks, called WinNet, including (i) Inter-Intra Period Encoder (I2PE) to transform 1D sequence into 2D tensor with long and short periodicity according to the predefined periodic window, (ii) Two-Dimensional Period Decomposition (TDPD) to model period-trend and oscillation terms, and (iii) Decomposition Correlation Block (DCB) to leverage the correlations of the period-trend and oscillation terms to support the prediction tasks by CNNs.

Time Series Time Series Forecasting