Abstract
In the era of 5G networks, traffic management is an essential task. Machine learning techniques can be utilised to provide solutions for traffic management in 5G networks. The traffic data can be maintained in a database and analysed using various machine learning techniques. In this work, a 3D CNN model is combined with an RNN model for analysing and classifying the network traffic into three classes of maximum, average and minimum traffic. The result proves that the combined 3D CNN and RNN model provides better classification of network traffic.
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