文献
J-GLOBAL ID:202102250831202889
整理番号:21A1731155
流れ入射角を考慮した機械学習応用に基づく海底パイプライン平衡洗掘深さの予測【JST・京大機械翻訳】
Prediction of submarine pipeline equilibrium scour depth based on machine learning applications considering the flow incident angle
著者 (7件):
Hu Ke
(School of Naval Architecture and Maritime, Zhejiang Ocean University, Zhoushan 316022, PR China)
,
Hu Ke
(Key Laboratory of Offshore Engineering Technology of Zhejiang Province, Zhoushan 316022, PR China)
,
Bai Xinglan
(School of Naval Architecture and Maritime, Zhejiang Ocean University, Zhoushan 316022, PR China)
,
Bai Xinglan
(Key Laboratory of Offshore Engineering Technology of Zhejiang Province, Zhoushan 316022, PR China)
,
Zhang Zhaode
(School of Naval Architecture and Maritime, Zhejiang Ocean University, Zhoushan 316022, PR China)
,
Zhang Zhaode
(Key Laboratory of Offshore Engineering Technology of Zhejiang Province, Zhoushan 316022, PR China)
,
Vaz Murilo A.
(Ocean Engineering Program, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil)
資料名:
Applied Ocean Research
(Applied Ocean Research)
巻:
112
ページ:
Null
発行年:
2021年
JST資料番号:
A0775B
ISSN:
0141-1187
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)