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.

Xehetasun bibliografikoak
Egile nagusia: Ahasan, Md Rakibul
Beste egile batzuk: Alam, Md. Golam Robiul
Formatua: Thesis
Hizkuntza:English
Argitaratua: Brac University 2022
Gaiak:
Anomaly detection
Supervised learning
KPI
Mobile Networks
SMOTE
Unsupervised learning
K-Means
DBSCAN
HDBSCAN
Autoencoder
Algorithms
Computer network architectures
Sarrera elektronikoa:http://hdl.handle.net/10361/17164

Internet

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

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