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Found 2 papers, 1 papers with code
ATFNet: Adaptive Time-Frequency Ensembled Network for Long-term Time Series Forecasting
To capitalize on both of these strengths, we propose ATFNet, an innovative framework that combines a time domain module and a frequency domain module to concurrently capture local and global dependencies in time series data.
A Novel Hybrid Framework for Hourly PM2.5 Concentration Forecasting Using CEEMDAN and Deep Temporal Convolutional Neural Network
For hourly PM2. 5 concentration prediction, accurately capturing the data patterns of external factors that affect PM2. 5 concentration changes, and constructing a forecasting model is one of efficient means to improve forecasting accuracy.
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