Design of a Fuzzy Linear Regression Model for Forecasting Transport Energy Demand: a case study of Iran

Taghizadeh Yazdi, Mohammad Reza; Shakouri Ganjavi, Hamed; Menhaj, Mohammad Bagher; Mehregan, Mohammad Reza; Kazemi, Aliyeh

doi:10.22059/imj.2014.52233

Design of a Fuzzy Linear Regression Model for Forecasting Transport Energy Demand: a case study of Iran

Document Type : Original Research Article

Authors

Mohammad Reza Taghizadeh Yazdi

Hamed Shakouri Ganjavi

Mohammad Bagher Menhaj

Mohammad Reza Mehregan

Aliyeh Kazemi

10.22059/imj.2014.52233

Abstract

In this paper, the energy demand of transport sector from 1385 to 1400 is forecasted based on Fuzzy Linear Regression (FLR) approach considering economic and social indicators. In order to analyze the influence of economic and social indicators on energy demand of transport sector, Gross Domestic Product (GDP), population and the total number of vehicles in 1372-1384 were regarded. In this research, the energy consumption may achieve a level of 625 MBOE per year by 1400.The results compared with the multiple regression method reveal much less mistakes. The average absolute error percentage reached from 12.33 % to 5.72 %.

Keywords

Fuzzy linear regression

Transport energy demand

forecasting