• Title of article

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

  • Author/Authors

    Hassanzadeh, Reza Department of Industrial Engineering - University College of Ayandegan , Hassanzadeh, Reza Department of Industrial Engineering - University College of Rouzbahan, Sari

  • Pages
    10
  • From page
    67
  • To page
    76
  • Abstract
    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
  • Keywords
    Forecast Gas , Consumption , ARIMA
  • Journal title
    Astroparticle Physics
  • Serial Year
    2017
  • Record number

    2442362