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.

Bibliografiset tiedot
Päätekijä: Ahasan, Md Rakibul
Muut tekijät: Alam, Md. Golam Robiul
Aineistotyyppi: Opinnäyte
Kieli:English
Julkaistu: Brac University 2022
Aiheet:
Anomaly detection
Supervised learning
KPI
Mobile Networks
SMOTE
Unsupervised learning
K-Means
DBSCAN
HDBSCAN
Autoencoder
Algorithms
Computer network architectures
Linkit:http://hdl.handle.net/10361/17164

Internet

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

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