… 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 …

… 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 …

… To compare forecasting results with the real value, with forecasting … the forecasting MAPE
and RMSE of the ARIMA-GARCH model are 0.045% and 0.071, and those of the ARIMA model …

… 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 …

… In this study, we implemented the ARIMA-GARCH model for forecasting the GDP of Ghana.
… , 2, 2) model show heteroscedasticity and therefore, we incorporate a GARCH (1, 1) model in …

… -term memory neural network. In addition, Yao et al. [35] presented a nonlinear hybrid method
for traffic flow forecasting, which uses the ARIMA-GARCH model to predict the similar and …

… ARIMA-GARCH model provides more accurate prediction with … applied ARIMA and GARCH
to predict crowd count using Wi-… ARIMA-GARCH to forecast mobile network traffic in Vietnam. …

… realized volatility first using for example ARIMA and then predict its residuals with ARCH to
have the first hybrid model implemented in this work denoted by ARIMA-GARCH (see Sect. …