a fuzzy regression model for energy consumption in textile industries

This paper introduces a fuzzy regression model for efficiently energy consumption estimation in textile industry of iran from 1980 to 2004. in order to get better performance, a preprocessing method, min-max method, is utilized to put data in a desired range. according to high fluctuations in this kind of industries, conventional methods are not capable of estimating energy consumption precisely. in both models, the training sample period covers 1980 to 1999 while the test period relates to 2000 to 2004.test results indicate that the proposed fuzzy regression is more precise than the conventional logarithmic regression technique in terms of mean absolute percentage error (mape), root mean square error (rmse), and mean absolute error (mae). this model and those results can undoubtedly play an effective role in the improvement and development of supply chain management, since they can be clearly employed in other industries.