文献
J-GLOBAL ID:202202277270612693
整理番号:22A1169622
5Gおよび6G品質サービス(QoS)を最適化するための連合深層学習エンパワー資源管理法【JST・京大機械翻訳】
A Federated Deep Learning Empowered Resource Management Method to Optimize 5G and 6G Quality of Services (QoS)
著者 (6件):
Alsulami Hemaid
(Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia)
,
Serbaya Suhail H.
(Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia)
,
Abualsauod Emad H.
(Department of Industrial Engineering, College of Engineering, Taibah University, 41411, Madina Almonawara, Saudi Arabia)
,
Othman Asem Majed
(Department of Industrial and Systems Engineering, College of Engineering, University of Jeddah, Jeddah 21959, Saudi Arabia)
,
Rizwan Ali
(Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia)
,
Jalali Asadullah
(American University of Afghanistan, Kabul, Afghanistan)
資料名:
Wireless Communications & Mobile Computing
(Wireless Communications & Mobile Computing)
巻:
2022
ページ:
Null
発行年:
2022年
JST資料番号:
W1338A
ISSN:
1530-8669
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)