چكيده به لاتين
Development and even permanence of most economical activities in developing countries are depended on energy supplying issues. Therefore, authorities in this countries try to forecast energy consumption and efficient planning in energy consumption guidance in order to control energy supply and demand in a proper way. Because of high value of transporting sector and its determinative impact on societies, it is counted as a development index between countries and progress and development of that has a big role on evolution of other industrial sections, agriculture and production. So today most of the scientists and experts in the economic sphere, recognize comprehensive progressing and development related to transport section growth. Different methods are suggested for modeling and predicting of future energy demand in transport section such as econometrics methods and artificial neural network (ANN) and metaheuristics. The focus of this thesis is to forecast future energy demand in internal road transportation by means of fuzzy linear regression (FLR) with triangular fuzzy parameters. In this study in addition of estimating energy demand subordinates in internal road transportation, it proceeds to propose a method for hypothesis test for fuzzy regression variables. Iran's road transportation industry is investigated as case study. After model estimation, MPFE, MAFE and RMSFE are used to test and measure model's efficiency and power in forecasting. Finally, with proposed method hypothesis test for fuzzy regression variables is implemented.
