In this work, we propose a methodology to improve the precision of cell traffic forecasting with a machine learning approach.
This work proposes a methodology to improve the precision of cell traffic forecasting with a machine learning approach, and selected the features and ...
In this work, we propose a methodology to improve the precision of cell traffic forecasting with a machine learning approach. To develop this methodology, ...
We propose two novel mobile traffic predictors. The first is a Mixture of Experts (MoE) model which yields significantly better peak prediction along with ...
Abstract—In this work, we propose a methodology to improve the precision of cell traffic forecasting with a machine learning approach.
Nov 21, 2024 · Due to these advancements, deep learning models are now utilized for network traffic classification and prediction. Long Short-Term Memory ...
Jul 12, 2023 · This paper proposes a network encryption traffic classification model that combines attention mechanisms and spatiotemporal features.
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The paper proposes an approach to the joint use of statistical and machine learning (ML) models to solve the problems of the precise reconstruction of ...
Apr 1, 2024 · The study found that SVM is more accurate in predicting high-dimensional traffic data, while MLPWD has higher accuracy in predicting low- ...
Nov 21, 2024 · This work is based on predicting future network traffic patterns and load through the implementation of machine learning methods applied based ...