… with state membership degree, and the wavelet neural network. The ARIMA-GARCH model
is used to predict the similar and volatile parts, and the other methods are adopted to predict …

… It can be seen that it is crucial to find the right model or method to predict the traffic flow. …
model and GARCH-M model, the ARIMA-GARCH-M hybrid model is constructed to predict the …

… ) detection in the analyzed network traffic with the use of a mixed statistical model (hybrid) …
for every model forecasting prediction intervals profiles (for example, 30 samples prediction …

… was investigated whether one is good enough as both orders for financial issues [57] and
the orders were set to one in [20], where ARIMA/GARCH model was adapted for network traffic …

… Conditional Heteroscedasticity (ARIMA-GARCH) was used for traffic flow prediction in
short-term time series that exhibit stationarity characteristics. However, the approach failed to …

… forecasting errors was seldom mentioned. In this study, a multiplicative seasonal ARIMA/GARCH …
appearing in mobile traffic series can be processed by GARCH models. Our proposed …

… the traditional models and the ARIMA-GARCH modeling … , then the ARIMA-GARCH modeling
approach is introduced, in … procedure are described, next the model results are analyzed, …

… The research in [33] uses an ARIMA/GARCH combination for network traffic modelling and
prediction. In this approach linear terms in the time series are captured by ARIMA model and …

… ARIMA model to be sufficient to forecast traffic flow. Bhardwaj et al. (2014) while predicting the
… of GARCH (1,1) is a fitted model forecast, since RMSE, MAE, and MAPE is low, and further …

… through ARIMA models. Although these models provide accurate forecasting over a short
time … paper we examine a hybrid ARIMA-GARCH model in order to forecast the volatility in the …