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Taghizadeh Yazdi, Mohammad Reza, Shakouri Ganjavi, Hamed, Menhaj, Mohammad Bagher, Mehregan, Mohammad Reza, Kazemi, Aliyeh. (1393). Design of a Fuzzy Linear Regression Model for Forecasting Transport Energy Demand: a case study of Iran. , 6(1), 23-34. doi: 10.22059/imj.2014.52233
Mohammad Reza Taghizadeh Yazdi; Hamed Shakouri Ganjavi; Mohammad Bagher Menhaj; Mohammad Reza Mehregan; Aliyeh Kazemi. "Design of a Fuzzy Linear Regression Model for Forecasting Transport Energy Demand: a case study of Iran". , 6, 1, 1393, 23-34. doi: 10.22059/imj.2014.52233
Taghizadeh Yazdi, Mohammad Reza, Shakouri Ganjavi, Hamed, Menhaj, Mohammad Bagher, Mehregan, Mohammad Reza, Kazemi, Aliyeh. (1393). 'Design of a Fuzzy Linear Regression Model for Forecasting Transport Energy Demand: a case study of Iran', , 6(1), pp. 23-34. doi: 10.22059/imj.2014.52233
Taghizadeh Yazdi, Mohammad Reza, Shakouri Ganjavi, Hamed, Menhaj, Mohammad Bagher, Mehregan, Mohammad Reza, Kazemi, Aliyeh. Design of a Fuzzy Linear Regression Model for Forecasting Transport Energy Demand: a case study of Iran. , 1393; 6(1): 23-34. doi: 10.22059/imj.2014.52233

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

Industrial Management Journal
مقاله 2، دوره 6، شماره 1، تیر 2014، صفحه 23-34    اصل مقاله (732.9 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/imj.2014.52233
نویسندگان
Mohammad Reza Taghizadeh Yazdi* ؛ Hamed Shakouri Ganjavi؛ Mohammad Bagher Menhaj؛ Mohammad Reza Mehregan؛ Aliyeh Kazemi
چکیده
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 %.
کلیدواژه‌ها
Fuzzy linear regression؛ Transport energy demand؛ forecasting
آمار
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