文献
J-GLOBAL ID:202202276530237731
整理番号:22A0773026
COVID-19時系列予測のための深層学習モデルと統計的方法の結合に基づく新しいアプローチ【JST・京大機械翻訳】
A novel approach based on combining deep learning models with statistical methods for COVID-19 time series forecasting
著者 (4件):
Abbasimehr Hossein
(Faculty of Information Technology and Computer Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran)
,
Paki Reza
(Faculty of Information Technology and Computer Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran)
,
Paki Reza
(School of Industrial and Information Engineering, Politecnico di Milano University, Milano, Italy)
,
Bahrini Aram
(Department of Engineering Systems and Environment, University of Virginia, Charlottesville, Virginia, USA)
資料名:
Neural Computing & Applications
(Neural Computing & Applications)
巻:
34
号:
4
ページ:
3135-3149
発行年:
2022年
JST資料番号:
W0703A
ISSN:
0941-0643
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
ドイツ (DEU)
言語:
英語 (EN)