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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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書誌詳細
主要な著者:	Fang, Jin, Guo, Xin, Liu, Yujia, Chang, Xiaokun, Fujita, Hamido, Wu, Jian
フォーマット:	論文
出版事項:	Elsevier Ltd 2023
主題:	T Technology (General)
オンライン･アクセス:	http://eprints.utm.my/106425/ http://dx.doi.org/10.1016/j.cie.2023.109667
タグ:	タグ追加タグなし, このレコードへの初めてのタグを付けませんか!

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