This paper focuses on the problem of cell anomaly detection, addressing partial and complete degradations in cell-service performance, and it proposes an ...
Ensemble Method for Cell Anomaly Detection. The proposed ensemble-method framework applies individ- ual univariate and multivariate methods to the training KPI.
This paper focuses on the problem of cell anomaly detection, addressing partial and complete degradations in cell-service performance, and it proposes an ...
This paper focuses on the problem of cell anomaly detection, addressing partial and complete degradations in cell-service performance, and it proposes an ...
The results suggest that the proposed ensemble method automatically and significantly improves the detection quality over univariate and multivariate ...
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Jan 1, 2023 · In addition, we used soft voting scheme ensemble learning based on three classifiers, i.e., DT, RF, and SVM, for anomaly detection. We also ...
In this paper we have applied Supervised Machine Learning (SML) to a set of long term observation time series from a Cellular/Wireless network.
We investigate different ensemble-learning approaches to enhance the detection of attacks and anomalies in network measurements.
Sep 30, 2022 · We propose an abnormal traffic detection method based on the stacking method and self-attention mechanism, which makes up for the shortcoming of the inability ...
In a related work, they have proposed ensemble method to compare different KPIs and cell performance using machine learning algorithm. We have applied DNN ...