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.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Ahasan, Md Rakibul
Άλλοι συγγραφείς: Alam, Md. Golam Robiul
Μορφή: Thesis
Γλώσσα:English
Έκδοση: Brac University 2022
Θέματα:
Anomaly detection
Supervised learning
KPI
Mobile Networks
SMOTE
Unsupervised learning
K-Means
DBSCAN
HDBSCAN
Autoencoder
Algorithms
Computer network architectures
Διαθέσιμο Online:http://hdl.handle.net/10361/17164

Διαδίκτυο

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

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