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.

Bibliografiska uppgifter
Huvudupphovsman: Ahasan, Md Rakibul
Övriga upphovsmän: Alam, Md. Golam Robiul
Materialtyp: Lärdomsprov
Språk:English
Publicerad: Brac University 2022
Ämnen:
Anomaly detection
Supervised learning
KPI
Mobile Networks
SMOTE
Unsupervised learning
K-Means
DBSCAN
HDBSCAN
Autoencoder
Algorithms
Computer network architectures
Länkar:http://hdl.handle.net/10361/17164

Internet

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

Liknande verk