3G and 4G paging success rate based mobile network anomaly detection using supervised and unsupervised learning

3G and 4G paging success rate based mobile network anomaly detection using supervised and unsupervised learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2022.

Bibliografische gegevens
Hoofdauteur: Ahasan, Md Rakibul
Andere auteurs: Alam, Md. Golam Robiul
Formaat: Thesis
Taal:English
Gepubliceerd in: Brac University 2022
Onderwerpen:
Anomaly detection
Supervised learning
KPI
Mobile Networks
SMOTE
Unsupervised learning
K-Means
DBSCAN
HDBSCAN
Autoencoder
Algorithms
Computer network architectures
Online toegang:http://hdl.handle.net/10361/17164

Internet

http://hdl.handle.net/10361/17164

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