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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| 主要な著者: | , , , , , |
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| フォーマット: | 論文 |
| 出版事項: |
Elsevier Ltd
2023
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| 主題: | |
| オンライン･アクセス: | http://eprints.utm.my/106425/ http://dx.doi.org/10.1016/j.cie.2023.109667 |
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