Providing optimal model of gasoline monthly consumption prediction in Iran using econometric models

Articles in Press

Document Type : Original Article

Authors

1 Industrial Engineering / Faculty of Industrial Engineering / Iran University of Science and Technology / Tehran / Iran

2 Faculty of Industrial Engineering, Iran University of Science and Technology, Tehran

Abstract

Gasoline is one of the strategic goods which due to the development of related industries, especially the increasing number of cars in traffic, growing demand for this petroleum product seems. So, precise and accurate gasoline consumption prediction is important in different periods. In this regard, in this paper various econometric methods such as Autoregressive, Moving Average, Auto Regressive Integrated Moving Average (ARIMA), exponential smoothing and Holt-Winters smoothing in last version of MINITAB 19 to predict the monthly consumption of gasoline. Given the complex nature of data on demand and consumption of energy carriers, especially fossil fuels such as gasoline and gas oil, and the importance of this issue, data on monthly gas consumption in the country during the years 1384 to 1396 were received. The results show the accuracy of Holt-Winters additive model in predicting monthly consumption of gasoline in the country has a very high accuracy compared to other models.

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Journal of Transportation Research

Articles in Press, Accepted Manuscript
Available Online from 10 August 2020

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