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.

Opis bibliograficzny
1. autor:	Ahasan, Md Rakibul
Kolejni autorzy:	Alam, Md. Golam Robiul
Format:	Praca dyplomowa
Język:	English
Wydane:	Brac University 2022
Hasła przedmiotowe:	Anomaly detection Supervised learning KPI Mobile Networks SMOTE Unsupervised learning K-Means DBSCAN HDBSCAN Autoencoder Algorithms Computer network architectures
Dostęp online:	http://hdl.handle.net/10361/17164

Podobne zapisy

LRFS: online shoppers’ behavior based efficient customer segmentation model
od: Khan, Riyo Hayat
Wydane: (2023)

A Study of gainful employment of learners receiving skills training in the informal sector using Machine Learning
od: Raizan, Syed Ahsan, i wsp.
Wydane: (2021)

Speech emotion detection using supervised, unsupervised and feature selection algorithms
od: Rifat, Abu Nuraiya Mahfuza Yesmin, i wsp.
Wydane: (2019)

Analysis on dengue severity using machine learning approach
od: Sayeed, Sanjana, i wsp.
Wydane: (2021)

Anomaly clustering based on correspondence analysis
od: Islam, Humayra
Wydane: (2018)

Anomaly detection In IoT using machine learning algorithms
od: Arko, Aritro Roy, i wsp.
Wydane: (2019)

Education content provider based on particular weaknesses of students: a unsupervised machine learning appro
od: Rahman, Shabab Intishar, i wsp.
Wydane: (2024)

Fake profile detection in social media using image processing and machine learning
od: Sen, Shuva, i wsp.
Wydane: (2021)

LRFMV: an efficient customer segmentation model for superstores
od: Toyeb, Md., i wsp.
Wydane: (2021)

Finding ideal geographical location for businesses using machine learning technique
od: Mahmud, Mir Ibtid, i wsp.
Wydane: (2022)

Classiﬁcation of damaged vegetation areas using convolutional neural network over satellite images
od: Haque, Samiha, i wsp.
Wydane: (2021)

Learning algorithms for anomaly detection from images
od: Ahmed, Tarem, i wsp.
Wydane: (2018)

Identification and comparative analysis of potholes using image processing algorithms
od: Anik, Fahim Shahriare, i wsp.
Wydane: (2018)

Supervision in thought and action /
od: Lucio, William H.
Wydane: (1979)

Customer segmentation using K-means
od: Mahdee, Nafis, i wsp.
Wydane: (2022)

Gene expression analysis using machine learning
od: Mostafa, Naﬁs
Wydane: (2021)

Automated intruder detection from image sequences using minimum volume sets
od: Ahmed, Tarem, i wsp.
Wydane: (2016)

Excellence in supervision : essential skills for the new supervisor /
od: Conlow, Rick
Wydane: (2004)

Classification of Bangla regional languages and recognition of artificial Bangla speech using deep learning
od: Hossain, Prommy Sultana
Wydane: (2022)

Introduction to creative supervision /
od: Burby, Raymond J., 1916-
Wydane: (1980)

Prediction of coronary heart diseases using supervised machine learning algorithms
od: Salam, Nazia Binte, i wsp.
Wydane: (2023)

Agricultural analysis and crop yield prediction of Habiganj using multispectral bands of satellite imagery with machine learning
od: Shahrin, Fariha, i wsp.
Wydane: (2021)

Detecting anomalies in human eyes using structural similarity index measurement
od: Jahan, Monwar, i wsp.
Wydane: (2019)

An introduction to basic supervision of people /
od: Burby, Raymond J., 1916-
Wydane: (1966)

The role of artificial intelligent in streamlining assurance and supervision procedures for CVC Finance Limited
od: Salman, Md. Mostafa
Wydane: (2024)

Implementation of neural network in game engine to create smart bot and behavior analysis
od: Shovon, Zamshed Khan, i wsp.
Wydane: (2018)

ML based performance assurance and VoC management of highly convergence mobile operator network.
od: Rahman, Md. Arifur
Wydane: (2024)

Performance analysis of intrusion detection systems using the PyCaret machine learning library on the UNSW-NB15 dataset
od: Abdullah, i wsp.
Wydane: (2021)

Automatic text summarization using Gensim Word2Vec and K-Means Clustering Algorithm
od: Haider, Mofiz Mojib, i wsp.
Wydane: (2021)

UAV assisted cooperative caching on network edge using multi agent Actor critic reinforcement learning
od: Araf, Sadman, i wsp.
Wydane: (2021)

Demystifying machine learning models for IOT attack detection with explainable AI
od: Muna, Rabeya Khatun, i wsp.
Wydane: (2021)

Identifying Bangla deceptive news using machine learning and deep learning algorithms
od: Piyal, Anindya Roy, i wsp.
Wydane: (2023)

Predicting effectiveness of marketing through analyzing emotional context in advertisement using deep learning
od: Arafat, Sheikh Mohammad, i wsp.
Wydane: (2021)

Brain tumor detection through image processing
od: Azmim, Tahaziba, i wsp.
Wydane: (2021)

Predicting crime using deep learning
od: Shihab, Muhammad Nafees, i wsp.
Wydane: (2024)

Assessment of procurement process of carriage rehabilitation project at Saidpur workshop implemented by Bangladesh railway based on Key Performance Indicators (KPI
od: Rahman , Md. Habibur
Wydane: (2021)

N.P.K. based crop suggesting model
od: Iftekher, Asif, i wsp.
Wydane: (2020)

Bangla number plate recognition from noisy video footage using deep learning
od: Chowdhury, Mahfuzur Rahman, i wsp.
Wydane: (2021)

The hundred-page machine learning /
od: Burkov, Andriy
Wydane: (2019)

An autoencoder-based decentralized clustering leveraging model aggregation fusion strategy
od: Hasan, Nahid
Wydane: (2024)