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.

Bibliographische Detailangaben
1. Verfasser: Ahasan, Md Rakibul
Weitere Verfasser: Alam, Md. Golam Robiul
Format: Abschlussarbeit
Sprache:English
Veröffentlicht: Brac University 2022
Schlagworte:
Anomaly detection
Supervised learning
KPI
Mobile Networks
SMOTE
Unsupervised learning
K-Means
DBSCAN
HDBSCAN
Autoencoder
Algorithms
Computer network architectures
Online Zugang:http://hdl.handle.net/10361/17164

Online

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

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