… Moreover, parallel to applying jointly with some nonlinear approaches (eg, ARIMA), some
hybrid models based on the ARIMA's foundation have been proposed. For instance, Fuzzy-…

… of constructing model based on wavelet transformation and LSTM network. Firstly, the … on
network traffic prediction. The prediction model based on wavelet transformation and LSTM …

… [10] proposed a traffic forecasting model based on modified ensemble … the prediction
accuracy of the network traffic and proposes an LSTM based on the network traffic prediction model …

… We propose a denoising method based on wavelet decomposition … a traffic flow prediction
model WT-2DCNN, which uses wavelet analysis to decompose the time-series data into …

… , a neural network model based on long … in network traffic prediction. Knowledge in the
source domain is transferred to the target domain using transfer learning, and a prediction model …

… model by improved particle swarm … model improves the accuracy of network traffic prediction,
and demonstrates the algorithm’s feasibility and effectiveness for network traffic prediction. …

… 2 Flow Prediction Model This section describes recurrent neural networks (RNN), which are
used for network traffic prediction, … networks (LSTM). On the basis of this, we put forward the …

… [2] have developed a prediction model based on the … Network (RNN) used for network traffic
prediction and introduces a special type of RNN: the Gated Recurrent Units (GRU) networks. …

… LSTM short-term traffic flow prediction model, the aim of this … model to predict short-term
traffic flows, and analyze the difference between its predictions and those of the LSTM model. …

… ML-based methods for network traffic prediction. The authors of [5] propose a framework
for network Traffic Matrix (TM) prediction based on Recurrent Neural Networks equipped with …