文献
J-GLOBAL ID:202102285452240180
整理番号:21A2386085
ビール工場排水支援酸性鉱山排水処理の最適化 応答曲面法と人工ニューラルネットワーク【JST・京大機械翻訳】
Optimising Brewery-Wastewater-Supported Acid Mine Drainage Treatment vis-a-vis Response Surface Methodology and Artificial Neural Network
著者 (5件):
Akinpelu Enoch A.
(Bioresource Engineering Research Group (BioERG), Cape Peninsula University of Technology, P.O. Box 652, Cape Town 8000, South Africa)
,
Ntwampe Seteno K. O.
(Water Pollution Monitoring and Remediation Initiatives Research Group, School of Chemical and Minerals Engineering, North-West University, P. Bag X60001, Potchefstroom 2520, South Africa)
,
Taiwo Abiola E.
(Department of Chemical Engineering, College of Engineering, Landmark University, PMB 1001, Omu Aran 240243, Nigeria)
,
Nchu Felix
(Bioresource Engineering Research Group (BioERG), Cape Peninsula University of Technology, P.O. Box 652, Cape Town 8000, South Africa)
,
Nchu Felix
(Department of Horticultural Sciences, Bellville Campus, Cape Peninsula University of Technology, Symphony Way, PO Box 1906, Bellville 7535, South Africa)
資料名:
Processes (Web)
(Processes (Web))
巻:
8
号:
11
ページ:
1485
発行年:
2020年
JST資料番号:
U7264A
ISSN:
2227-9717
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
スイス (CHE)
言語:
英語 (EN)