Forecasting the fuel consumption based on the fuzzy linear regression models


  • Nadia Rasouli PhD. Candidate, Industrial Engineering, Tarbiat Modares University, Tehran, Iran.


The growth and survival of most economic activities in developing countries depend on the energy supply issue. Therefore, government authorities try to favorably control energy supply and demand parameters by predicting energy consumption and proper planning to guide consumption as carefully as possible. Crude petroleum and petroleum products form a major part of energy carriers in Iran and thus the experts have had to take essential steps towards forecasting and planning in this regard. In this work, the demand for petroleum products including gasoline, gasoil, fuel oil, kerosene and LPG have been forecasted by linear regression, regression using the Cobb-Douglas function and fuzzy linear regression models considering the effective parameters. Data for the years 1996-2011 period have been used for the assessment of regression model and he 2012-12016 data have been used to select the appropriate model and the check its validity. Finally, the demand for petroleum products in 2017-2036 has been forecasted using the most appropriate model.

Keywords: Forecasting; Petroleum products; Fuzzy linear regression; Cobb-Douglas function; linear regression function.




How to Cite

Rasouli, N. (2018). Forecasting the fuel consumption based on the fuzzy linear regression models. International Journal of Engineering Science and Generic Research, 4(3). Retrieved from