文献
J-GLOBAL ID:202202231692616448
整理番号:22A0922634
数値天気予報を補正するための新しいハイブリッド深層学習アルゴリズムを用いた短期風速予測法【JST・京大機械翻訳】
A short-term wind speed prediction method utilizing novel hybrid deep learning algorithms to correct numerical weather forecasting
著者 (7件):
Han Yan
(School of Civil Engineering, Changsha University of Science and Technology, Changsha 410083, China)
,
Mi Lihua
(School of Civil Engineering, Changsha University of Science and Technology, Changsha 410083, China)
,
Shen Lian
(School of Civil Engineering, Changsha University, Changsha 410083, China)
,
Cai C.S.
(Department of Bridge Engineering, School of Transportation, Southeast University, Nanjing, 211189, China)
,
Liu Yuchen
(School of Civil Engineering, Changsha University of Science and Technology, Changsha 410083, China)
,
Li Kai
(School of Civil Engineering, Changsha University of Science and Technology, Changsha 410083, China)
,
Xu Guoji
(Department of Bridge Engineering, Southwest Jiaotong University, Chengdu 610065, China)
資料名:
Applied Energy
(Applied Energy)
巻:
312
ページ:
Null
発行年:
2022年
JST資料番号:
A0097A
ISSN:
0306-2619
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)