文献
J-GLOBAL ID:202202244875862518
整理番号:22A1036981
アンサンブル学習を用いた鉄鋼産業における需要予測へのアプローチ【JST・京大機械翻訳】
An Approach for Demand Forecasting in Steel Industries Using Ensemble Learning
著者 (9件):
Raju S. M. Taslim Uddin
(Department of Computer Science and Engineering, Khulna University of Engineering & Technology, Khulna 9203, Bangladesh)
,
Sarker Amlan
(Department of Computer Science and Engineering, Daffodil International University, Dhaka 1207, Bangladesh)
,
Das Apurba
(Department of Industrial Engineering and Management, Khulna University of Engineering & Technology, Khulna 9203, Bangladesh)
,
Islam Md. Milon
(Department of Computer Science and Engineering, Khulna University of Engineering & Technology, Khulna 9203, Bangladesh)
,
Al-Rakhami Mabrook S.
(Research Chair of Pervasive and Mobile Computing, Information Systems Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia)
,
Al-Amri Atif M.
(Research Chair of Pervasive and Mobile Computing, Information Systems Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia)
,
Al-Amri Atif M.
(Software Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia)
,
Mohiuddin Tasniah
(Department of Computer Science and Engineering, Military Institute of Science and Technology, Dhaka 1216, Bangladesh)
,
Albogamy Fahad R.
(Computer Sciences Program, Turabah University College, Taif University, Taif 21944, Saudi Arabia)
資料名:
Complexity
(Complexity)
巻:
2022
ページ:
Null
発行年:
2022年
JST資料番号:
W2044A
ISSN:
1076-2787
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)