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.

Podrobná bibliografie
Hlavní autor: Ahasan, Md Rakibul
Další autoři: Alam, Md. Golam Robiul
Médium: Diplomová práce
Jazyk:English
Vydáno: Brac University 2022
Témata:
Anomaly detection
Supervised learning
KPI
Mobile Networks
SMOTE
Unsupervised learning
K-Means
DBSCAN
HDBSCAN
Autoencoder
Algorithms
Computer network architectures
On-line přístup:http://hdl.handle.net/10361/17164

Internet

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

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