In this paper, we experiment with several different forecasting approaches for Internet traffic
and a scheme for their evaluation. First the existence of properties such as Short or Long …

This paper investigates the use of ensembles of artificial neural networks in predicting long-
term Internet traffic. It discusses a method for collecting traffic information based on flows …

This paper compares four different artificial neural network approaches for computer network
traffic forecast, such as: 1) multilayer perceptron (MLP) using the backpropagation as …

In the era of the digital world. The communication and the use the internet is an important
role in today's society. As a result, the number of users networks traffic increases but not …

Internet traffic prediction is an important task for many applications, such as adaptive
applications, congestion control, admission control, anomaly detection and bandwidth …

This article presents three methods to forecast accurately the amount of traffic in TCP/IP
based networks: a novel neural network ensemble approach and two important adapted …

Prediction of Internet traffic time series data (TSD) is a challenging research problem, owing
to the complicated nature of TSD. In literature, many hybrids of auto-regressive integrated …

The forecast of Internet traffic is an important issue that has received few attention from the
computer networks field. By improving this task, efficient traffic engineering and anomaly …

In this paper we have applied the adaptive neuro-fuzzy inference system (ANFIS) which is
realized by an appropriate combination of fuzzy systems and neural networks for forecasting …

The advance knowledge of future traffic load is helpful for network service providers to
optimize the network resource and to recover the demand criteria. This paper presents the …