Forecasting the gasoline consumption in Iran’s transportation sector by ARIMA method

Publish Year: 1402
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:

JR_EES-11-4_004

تاریخ نمایه سازی: 31 تیر 1403

Abstract:

Transportation is one of the important bases of the national economy of any country. The development of the transportation sector has been accompanied by economic growth. In developing countries, the development of the transportation sector and the increasing number of vehicles increase energy consumption in this sector. Therefore, the management and energy supply of this sector are two of the main priorities of the governments in these countries. In this research, taking into account the data related to the gross domestic product, the number of gasoline cars produced, the number of passengers within and outside the province, and the price of gasoline, a regression equation was written using the least squares method to determine the effect of these components on consumption. Gasoline should be evaluated. Furthermore, with Iran's gasoline consumption data from ۱۹۶۲ to ۲۰۲۱, we have forecast the gasoline consumption between ۲۰۲۲ and ۲۰۳۱ with the ARIMA method. The research results show that between ۲۰۲۱ and ۲۰۲۲, Iran's gasoline consumption had a downward trend; its amount was -۰.۴۵%; and it had an upward trend from ۲۰۲۳ to ۲۰۳۱; it grew by ۵۲.۰۹% between these years.

Authors

Farhad Maleki

Department of Energy Engineering and Physics, Energy System Engineering, Amirkabir University, Tehran, Iran

Atefeh behzadi Forough

Department of Energy Engineering and Physics, Amirkabir University, Tehran, Iran

Zahra Akbari

Department of Energy Engineering and Physics, Energy System Engineering, Amirkabir University, Tehran, Iran

Pegah Manafzadeh

Department of Energy Engineering and Physics, energy system Engineering, Amirkabir University, Tehran, Iran

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  • Jia, S., et al., Review of Transportation and Energy Consumption ...
  • Mačiulis, A., A.V. Vasiliauskas, and G. Jakubauskas, The impact of ...
  • Zarifi, F., et al., Current and future energy and exergy ...
  • Sandoval-García, E., Y. Matsumoto, and D. Sánchez-Partida, Data and energy ...
  • Mohsin, M., et al., Integrated effect of energy consumption, economic ...
  • Samaras, Z. and I. Vouitsis, Energy Consumption of Transport Modes, ...
  • Moshiri, S., Consumer responses to gasoline price and non-price policies. ...
  • Sadeghi, M. and H. Mirshojaeian Hosseini, Integrated energy planning for ...
  • Ghorbani, N., A. Aghahosseini, and C. Breyer, Assessment of a ...
  • Moshiri, S. Energy price reform and energy efficiency in Iran. ...
  • Statistics of the consumption of energy-generating petroleum products in the ...
  • Omrani, H., K. Shafaat, and A. Alizadeh, Integrated data envelopment ...
  • Hosseini Nasab, E., et al., An analysis of energy consumption ...
  • About energy subsidy in Iran, hidden subsidy and its considerations ...
  • Cervero, R., Short-run forecasting of highway gasoline consumption in the ...
  • Ediger, V.Ş. and S. Akar, ARIMA forecasting of primary energy ...
  • Li, Z., J.M. Rose, and D.A. Hensher, Forecasting automobile petrol ...
  • Akpinar, M. and N. Yumusak. Forecasting household natural gas consumption ...
  • Mahia, F., et al. Forecasting Electricity Consumption using ARIMA Model. ...
  • Güngör, B.O., H.M. Ertuğrul, and U. Soytaş, Impact of Covid-۱۹ ...
  • DASTJERDI, A.M. and B.N. Araghi, Fuel Consumption Management in the ...
  • Zhang, G.P., Time series forecasting using a hybrid ARIMA and ...
  • Brockwell, P.J. and R.A. Davis, Introduction to time series and ...
  • Burton, A.L., OLS (Linear) regression. The Encyclopedia of Research Methods ...
  • Statistical yearbook of Iran. ۲۰۲۰: Statistical Center of Iran ...
  • Fattah, J., et al., Forecasting of demand using ARIMA model. ...
  • Oğuz, M.E., Forecasting Turkey's sectoral energy demand. ۲۰۱۳, Middle East ...
  • https://www.tgju.org/archive/price_dollar_rl. [cited ۲۰۲۲ November,۱۴] ...
  • نمایش کامل مراجع