Real-time mobile broadband quality of service prediction using AI-driven customer-centric approach

Real-time mobile broadband quality of service prediction using AI-driven customer-centric approach

<p>Statistical methods employed in evaluating the quality of service (performance) of mobile broadband (MBB) networks face drawbacks relating to the accurate and reliable processing of the huge amounts of heterogenous real time traffic data generated from MBB networks. Since the traffic patter...

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Bibliographic Details
Main Authors: Ayokunle A. Akinlabi, Folasade M. Dahunsi, Jide J. Popoola, Lawrence B. Okegbemi
Format: Article
Language:English
Published: Academy Publishing Center 2025-06-01
Series:Advances in Computing and Engineering
Subjects:
cellular network: mobile broadband
quality of service
machine learning
crowdsourcing
extreme gradient boosting
random forest
support vector machine
Online Access:http://apc.aast.edu/ojs/index.php/ACE/article/view/1332
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http://apc.aast.edu/ojs/index.php/ACE/article/view/1332

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