Forecasting the Energy Consumption Growth in Iran’s Industrial Sector Using the Fuzzy Linear Regression Method
Subject Areas : International Journal of Industrial Mathematicsعلیرضا اقبالی 1 , رضا یوسفی حاجی اباد 2
1 - استادیار گروه اقتصاد پیام نور
2 - استادیار گروه اقتصاد دانشگاه پیام نور
Keywords: Energy Demand, Fuzzy Regression, Forecasting, Energy Carriers, Industry,
Abstract :
Regression analysis is a widely used method for investigating relationships between one or more response variables and a set of explanatory variables. This analysis is based on the assumption of the accuracy of the studied variables and the observations related to them, and finally, it specifies the relationships between the variables. in modeling the forecast of energy consumption growth in economic sectors; Generally, the observations are imprecise or the relationships are vague and the relationship between the response variable and the input variables are not precise and well defined. Therefore, it is necessary to use methods of fitting functions that explain the ambiguous structure of data and the relationships between them; Fuzzy regression model, which describes the relationship between output and input data with a fuzzy function. According to this, the purpose of the present study is to forecast the growth rate of energy consumption in Iran's industrial sector using data from 1997 to 2019 by the fuzzy linear regression method. To do so, we collected the necessary statistics and information, and then forecasted the consumption of gas and petroleum products in Iran's industrial sector by 2029. Overall, the results of this research indicate that the growth of gas demand in Industry sector will be positive over time; even though it will have a slow slope. Also, the demand for petroleum products in this sector will be almost constant over time and will not fluctuate much. In addition, electricity demand will experience positive growth as the other parameter under study.
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