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.

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Ahasan, Md Rakibul
مؤلفون آخرون:	Alam, Md. Golam Robiul
التنسيق:	أطروحة
اللغة:	English
منشور في:	Brac University 2022
الموضوعات:	Anomaly detection Supervised learning KPI Mobile Networks SMOTE Unsupervised learning K-Means DBSCAN HDBSCAN Autoencoder Algorithms Computer network architectures
الوصول للمادة أونلاين:	http://hdl.handle.net/10361/17164

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