文献
J-GLOBAL ID:202202271784857819
整理番号:22A0919504
雑音条件下での熱可塑性複合材料管の損傷検出のための機械学習法【JST・京大機械翻訳】
Machine learning methods for damage detection of thermoplastic composite pipes under noise conditions
著者 (9件):
Bao Xingxian
(School of Petroleum Engineering, China University of Petroleum (East China), Qingdao, 266580, China)
,
Bao Xingxian
(National Engineering Laboratory of Offshore Geophysical and Exploration Equipment, China University of Petroleum (East China), Shandong, 266580, China)
,
Wang Zhichao
(School of Petroleum Engineering, China University of Petroleum (East China), Qingdao, 266580, China)
,
Fu Dianfu
(CNOOC Research Institute Ltd, Beijing, 100028, China)
,
Shi Chen
(School of Ocean Engineering, Harbin Institute of Technology at Weihai, Weihai, 264209, China)
,
Iglesias Gregorio
(MaREI, Environmental Research Institute & School of Engineering, University College Cork, College Road, Cork, Ireland)
,
Iglesias Gregorio
(University of Plymouth, School of Engineering, Marine Building, Drake Circus, Plymouth, PL4 8AA, United Kingdom)
,
Cui Hongliang
(Qingdao Pegasus Photoelectric Technology Co Ltd, Shandong, 266114, China)
,
Sun Zhengyi
(Qingdao Pegasus Photoelectric Technology Co Ltd, Shandong, 266114, China)
資料名:
Ocean Engineering
(Ocean Engineering)
巻:
248
ページ:
Null
発行年:
2022年
JST資料番号:
D0597A
ISSN:
0029-8018
CODEN:
OCENBQ
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)