… presentation for the traffic characteristics in both time and frequency domain. We also
demonstrate that the prediction performance of the k-factor GARMA model outperforms that of the …

… network, it has obtained extensive attention because of its large capacity and low cost. Network
traffic prediction is important for network … This paper proposes a network traffic prediction …

… We start by analyzing real-time traffic data collection, referring network state … useful traffic
prediction outputs that should contribute to understand the panorama verified on a road network…

… In this paper we would like to propose a new approach, the neural network approach, for
traflic prediction. It is well known that neural networks are capable of performing non-linear …

… and analyze a new network traffic prediction methodology, based on the ‘frequency domain’
traffic analysis and filtering, with the objective of enhancing the network anomaly detection …

… This article deals with the problem of real-time modelling and prediction of motorway traffic.
Conditional independence relationships and ideas of Bayesian forecasting are proposed …

… could adapt the network traffic change by self-learning. To improve the prediction accuracy,
we propose a new hybrid network traffic prediction method based on the combination of the …

… In this paper, we study the mobile traffic of an LTE base station and we design a system
for the traffic prediction using Recurrent Neural Networks. The mobile traffic information is …

… low accuracy of traditional network traffic prediction methods, a prediction method based on
… But many useless neurons in EM-ELM have little influences on the final network output, and …

… network traffic matrix prediction performance with the aim of having a high accuracy prediction
… Before describing the proposed models, a short overview of the different neural network …