Time Series Models to Predict the Monthly and Annual Consumption of Natural Gas in Iran

Journal of Industrial Strategic Management

مقاله 4، دوره 2، شماره 2، مرداد 2017، صفحه 67-76   

نوع مقاله: Original Article

نویسندگان

Arash Farrokhi¹؛ Reza Hassanzadeh^{* 2}

¹Department of Industrial Engineering, University College of Ayandegan, Tonekabon, Iran

²Department of Industrial Engineering, University College of Rouzbahan, Sari,, Iran, Iran

چکیده

Considering the fact that natural gas is a widely used energy source,  the prediction of its consumption can be useful (Derek LAM, 2013). As Iran has one of the largest gas reserves in the world, its consumption in the country can affect the worldwide price of gas, Therefore, the current research is useful both from economic and environmental point of view.
The goal of the study is to select the best model for the prediction of gas consumption. To achieve the goal time series analysis are used.   The findings indicate that ARIMA (0, 1, 0) is the best model for the prediction of annual gas consumption, while SARIMA (1, 0, 0) (1, 1, 0) for the prediction of monthly gas consumption

کلیدواژه‌ها

Forecast Gas؛ Consumption؛ ARIMA؛ SARIMA