文献
J-GLOBAL ID:202202291292401658
整理番号:22A0105399
有毒ガス漏洩事故時の安全避難経路のための深層ニューラルネットワークベース最適化フレームワーク【JST・京大機械翻訳】
Deep Neural Network-based Optimization Framework for Safety Evacuation Route during Toxic Gas Leak Incidents
著者 (6件):
Seo Seung-Kwon
(School of Chemical Engineering & Materials Science, Chung-Ang University, Seoul 06979, Republic of Korea)
,
Yoon Young-Gak
(Process Engineering Team, Samsung Engineering, Seoul 05288, Republic of Korea)
,
Lee Ju-sung
(School of Chemical Engineering & Materials Science, Chung-Ang University, Seoul 06979, Republic of Korea)
,
Na Jonggeol
(Department of Chemical Engineering and Materials Science, Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul 03760, Republic of Korea)
,
Lee Chul-Jin
(School of Chemical Engineering & Materials Science, Chung-Ang University, Seoul 06979, Republic of Korea)
,
Lee Chul-Jin
(Department of Intelligent Energy and Industry, Chung-Ang University, Seoul 06979, Republic of Korea)
資料名:
Reliability Engineering & System Safety
(Reliability Engineering & System Safety)
巻:
218
号:
PA
ページ:
Null
発行年:
2022年
JST資料番号:
D0980B
ISSN:
0951-8320
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
イギリス (GBR)
言語:
英語 (EN)