… Abstract- High-speed network traffic prediction is considered as the core of the preventive …
neural network (ANN) architectures, multilayer perceptron (MLP) and fuzzy neural network (…

… network and a temporal convolutional network (TCN). This article proposes a novel hybrid
prediction … (ST-LSTM) for such network traffic prediction, which synergistically combines the …

… The problem of network traffic prediction can be regarded as the problem of time series …
This paper summarizes the relative research on network traffic prediction. The prediction model …

… Section III presents the system model of network traffic prediction. In Section IV, we
present the RLbased network traffic prediction mechanism for IIoTs. Section V describes our …

… PREDICTION MODEL This section describes Recurrent Neural Networks (RNN) , which used
for network traffic prediction. … of RNN, Long Short Term Memory networks (LSTM). On the …

… This article aims to improve the prediction accuracy of the network traffic and proposes an
LSTM based on the network traffic prediction model (LNTP). The main contributions of the …

… We will now discuss the different types of prediction models that have been used for traffic
prediction in the past. The field of traffic prediction has existed for almost five decades and …

… In this paper we propose a new network traffic prediction model based on non-linear time …
our models’ prediction. We show that our model can capture prominent traffic characteristics, …

… Network traffic analysis and modeling play a major role in charactering network performance,
… Models that accurately capture the salient characteristics of the traffic is useful for analysis …

… the network traffic. Against this backdrop, this paper will review past research conducted
on hybrid network traffic prediction … of existing hybrid network prediction models which use …