文献
J-GLOBAL ID:202202213950713775
整理番号:22A0718625
LSTM深層ニューラルネットワークにもとづく船舶の操船運動の同定モデリングと予測
Identification modeling and prediction of ship maneuvering motion based on LSTM deep neural network
著者 (8件):
Jiang Yan
(School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, China)
,
Hou Xian-Rui
(School of Ocean Science and Engineering, Shanghai Maritime University, Shanghai, China)
,
Wang Xue-Gang
(CCCC Fourth Harbor Engineering Institute Co., Ltd., Guangzhou, China)
,
Wang Xue-Gang
(Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China)
,
Wang Zi-Hao
(School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, China)
,
Yang Zhao-Long
(School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, China)
,
Zou Zao-Jian
(School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, China)
,
Zou Zao-Jian
(State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai, China)
資料名:
Journal of Marine Science and Technology (Web)
(Journal of Marine Science and Technology (Web))
巻:
27
号:
1
ページ:
125-137
発行年:
2022年
JST資料番号:
U1597A
ISSN:
0948-4280
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)