An attention-based deep learning model for multi-horizon time series forecasting by considering periodic characteristic
Recently, transformer-based models have exhibited great performance in multi-horizon time series forecasting tasks. However, the core module of these models, the self-attention mechanism, is insensitive to the temporal order and suffers from attention dispersion over long time sequences. These limit...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Published: |
Elsevier Ltd
2023
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| Subjects: | |
| Online Access: | http://eprints.utm.my/106425/ http://dx.doi.org/10.1016/j.cie.2023.109667 |
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