文献
J-GLOBAL ID:202002249805408532
整理番号:20A2797072
都市火災状況予測:時空間動力学による深層シーケンス学習【JST・京大機械翻訳】
Urban Fire Situation Forecasting: Deep sequence learning with spatio-temporal dynamics
著者 (6件):
Jin Guangyin
(College of System Engineering, National University of Defense Technology, Changsha, China)
,
Wang Qi
(College of System Engineering, National University of Defense Technology, Changsha, China)
,
Zhu Cunchao
(College of System Engineering, National University of Defense Technology, Changsha, China)
,
Feng Yanghe
(College of System Engineering, National University of Defense Technology, Changsha, China)
,
Huang Jincai
(College of System Engineering, National University of Defense Technology, Changsha, China)
,
Hu Xingchen
(College of System Engineering, National University of Defense Technology, Changsha, China)
資料名:
Applied Soft Computing
(Applied Soft Computing)
巻:
97
号:
PB
ページ:
Null
発行年:
2020年
JST資料番号:
W2175A
ISSN:
1568-4946
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)