Annual Automobile Sales Prediction Using ARIMA Model

ATM dynamic bandwidth allocation using F-ARIMA prediction model

Measurements of high-speed network traffic have shown that traffic data exhibits a high degree of self-similarity. Traditional traffic models such as AR and ARMA are not able to capture this long-range-dependence making them ineffective for the traffic prediction task. In this paper, we apply the fractional ARIMA (F-ARIMA) model to predict one-step-ahead traffic value at different time scales. ...

Traffic Modeling and Prediction using ARIMA/GARCH Model

The predictability of network traffic is a significant interest in many domains such as congestion control, admission control, and network management. An accurate traffic prediction model should have the ability to capture prominent traffic characteristics, such as long-range dependence (LRD) and self-similarity in the large time scale, multifractal in small time scale. In this paper we propose...

Prediction of the Surface Run off in Semirom Mehregerd Watershed Using ARIMA Model

By understanding the temporal and spatial variations of water resources in a region, the better management and planning of water resources and water consumptions can be done. Time series modeling, if used correctly, will lead to acceptable results in this regard. For this purpose, the monthly runoff time series for 28 years was prepared at the hydrometric stations of Mehregerd region and the pr...

A Novel Divide-and-Conquer Model for CPI Prediction Using ARIMA, Gray Model and BPNN

Wind Speed Prediction Using a Univariate ARIMA Model and a Multivariate NARX Model

Two on step ahead wind speed forecasting models were compared. A univariate model was developed using a linear autoregressive integrated moving average (ARIMA). This method’s performance is well studied for a large number of prediction problems. The other is a multivariate model developed using a nonlinear autoregressive exogenous artificial neural network (NARX). This uses the variables: barom...