Machine-Learning-Based 5G Network Function Scaling via Black- and White-Box KPIs-Reference-Cited by-同舟云学术

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Machine-Learning-Based 5G Network Function Scaling via Black- and White-Box KPIs

Published:2023-06-13 Issue: Volume: Page:
ISSN:
Container-title:2023 21st Mediterranean Communication and Computer Networking Conference (MedComNet)
language:
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Author:

Bolla Raffaele¹,Bruschi Roberto¹,Davoli Franco¹,Lombardo Chiara²,Pajo Jane Frances³,Siccardi Beatrice⁴

Affiliation:

1. DITEN - University of Genoa,CNIT - S2N National Lab,Genoa,Italy

2. CNIT - S2N National Lab,Genoa,Italy

3. Telenor Research,Fornebu,Norway

4. DITEN - University of Genoa,Genoa,Italy

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10168827/10168806/10168859.pdf?arnumber=10168859

Reference25 articles.

1. TensorFlow,0

2. Scikit-learn,0

3. PyTorch,0

4. Keras,0

5. Comparison of Econometric Models and Artificial Neural Networks Algorithms for the Prediction of Baltic Dry Index

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1. Next-Gen Industry 4.0 with 5G: Enabling Secure and High-Performance Services for Critical Infrastructure;2024 7th International Balkan Conference on Communications and Networking (BalkanCom);2024-06-03

2. Assessment of Security KPIs for 5G Network Slices for Special Groups of Subscribers;Big Data and Cognitive Computing;2023-10-26

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