Prediction of University Network Traffic Using Deep Learning Method

Abstract

The paper goes over what would happen when deep learning methods are implemented for University Network Traffic. In order to predict the outcome, the paper will compare the network before the implementation of deep learning and after the implementation of deep learning. If the results show an increase in data transfer speed after the implementation of deep learning, it suggests that the implementation of deep learning in any network system will most likely improve the data transfer speed. The paper first defines what deep learning is. It then utilizes different methods of deep learning in order to train the system. The system will go through the training phase, testing phase, and the prediction phase in order to familiarize it with the current network system. Once it understands the network system, it will find the optimized network system in order to improve the speed of network connection.