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Machine Learning Based Network Status Detection and Fault Localization
2021
IEEE Transactions on Instrumentation and Measurement
Although the autonomous detection of network status and localization of network faults can be a valuable tool for network and service operators, very few works have investigated this subject. As a result in today's networks, fault detection and localization remains a mostly-manual process. In this paper, we propose a Machine Learning (ML) method that can automatically detect the status of a network and localize faults. Our method uses Decision Tree, Gradient Boosting (GB), and XGBoost (XGB) ML
doi:10.1109/tim.2021.3094223
fatcat:zq7wiscuhffx7cxyixb6yrnlmy