Regional Correlation Aided Mobile Traffic Prediction with Spatiotemporal Deep Learning-Reference-Cited by-同舟云学术

Regional Correlation Aided Mobile Traffic Prediction with Spatiotemporal Deep Learning

Published:2024-01-06 Issue: Volume: Page:566-569
ISSN:
Container-title:2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)
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Author:

Park JeongJun¹,Mwasinga Lusungu J.²,Yang Huigyu³,Raza Syed M.¹,Le Duc-Tai⁴,Kim Moonseong⁵,Chung Min Young¹,Choo Hyunseung¹

Affiliation:

1. Sungkyunkwan University,Department of Electrical and Computer Engineering,Suwon,Korea

2. Sungkyunkwan University,Department of Computer Science and Engineering,Suwon,Korea

3. Sungkyunkwan University,Department of Superintelligence Engineering,Suwon,Korea

4. College of Computing and Informatics, Sungkyunkwan University,Suwon,Korea

5. Seoul Theological University,Department of IT Convergence Software,Bucheon,Korea

Publisher

IEEE

Link

Reference9 articles.

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1. Federated Learning-Driven Edge AI for Enhanced Mobile Traffic Prediction;NOMS 2024-2024 IEEE Network Operations and Management Symposium;2024-05-06