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.

Bibliografski detalji
Glavni autor:	Ahasan, Md Rakibul
Daljnji autori:	Alam, Md. Golam Robiul
Format:	Disertacija
Jezik:	English
Izdano:	Brac University 2022
Teme:	Anomaly detection Supervised learning KPI Mobile Networks SMOTE Unsupervised learning K-Means DBSCAN HDBSCAN Autoencoder Algorithms Computer network architectures
Online pristup:	http://hdl.handle.net/10361/17164

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