文献
J-GLOBAL ID:202202290790083864
整理番号:22A0776434
河川システムの予測浮遊土砂負荷に対する種々の機械学習アプローチ性能の比較:マレーシアにおける事例研究【JST・京大機械翻訳】
A comparison of various machine learning approaches performance for prediction suspended sediment load of river systems: a case study in Malaysia
著者 (8件):
Hanoon Marwah Sattar
(College of Technical Engineering, Islamic University, Najaf, Iraq)
,
Hanoon Marwah Sattar
(College of Science, Al Muthanna University, Samawah, Al-Muthanna, Iraq)
,
Abdullatif B Alharazi Abdulhadi
(College of Engineering, Universiti Tenaga Nasional (UNITEN), Selangor, Malaysia)
,
Ahmed Ali Najah
(Institute of Energy Infrastructure (IEI), Universiti Tenaga Nasional (UNITEN), Selangor, Malaysia)
,
Razzaq Arif
(College of Technical Engineering, Islamic University, Najaf, Iraq)
,
Birima Ahmed H.
(Department of Civil Engineering, College of Engineering, Qassim University, Unaizah, Saudi Arabia)
,
El-Shafie Ahmed
(Department of Civil Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia)
,
El-Shafie Ahmed
(National Water and Energy Center, United Arab Emirate University, Al Ain, United Arab Emirates)
資料名:
Earth Science Informatics
(Earth Science Informatics)
巻:
15
号:
1
ページ:
91-104
発行年:
2022年
JST資料番号:
W4300A
ISSN:
1865-0473
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)