文献
J-GLOBAL ID:201902269223834379
整理番号:19A1575204
NF/RO膜濾過中の汚損成長とフラックス低下をモデル化するためのディープニューラルネットワーク【JST・京大機械翻訳】
Deep neural networks for modeling fouling growth and flux decline during NF/RO membrane filtration
著者 (6件):
Park Sanghun
(School of Urban Environmental Engineering, Ulsan National Institute of Science and Technology, UNIST-gil 50, Ulsan, 44919, Republic of Korea)
,
Baek Sang-Soo
(School of Urban Environmental Engineering, Ulsan National Institute of Science and Technology, UNIST-gil 50, Ulsan, 44919, Republic of Korea)
,
Pyo JongCheol
(School of Urban Environmental Engineering, Ulsan National Institute of Science and Technology, UNIST-gil 50, Ulsan, 44919, Republic of Korea)
,
Pachepsky Yakov
(Environmental Microbial and Food Safety Laboratory, USDA-ARS, Beltsville, MD, USA)
,
Park Jongkwan
(School of Urban Environmental Engineering, Ulsan National Institute of Science and Technology, UNIST-gil 50, Ulsan, 44919, Republic of Korea)
,
Cho Kyung Hwa
(School of Urban Environmental Engineering, Ulsan National Institute of Science and Technology, UNIST-gil 50, Ulsan, 44919, Republic of Korea)
資料名:
Journal of Membrane Science
(Journal of Membrane Science)
巻:
587
ページ:
Null
発行年:
2019年
JST資料番号:
E0669A
ISSN:
0376-7388
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)