Fuzzy Logic Application In Green Transport - Prediction Of Freight Train Energy Consumption

Rail freight transport is one of the most preferred modes of green transport since it emits three times less CO2 and particulates per ton-mile than road transport. Train energy consumption is the biggest issue related to rail traction costs. Data about freight trains energy consumption per year are not possible to define precisely, so it is convenient to use fuzzy logic as a tool for data prediction. In order to predict it, we provide Wang - Mendel method for combining both numerical and linguistic information into a common framework - a fuzzy rule base. Relevant input variables are: freight train kilometers, average freight trains weight and non-productive kilometers. The output variable from the defined fuzzy logic system is average energy consumption per year for rail freight transport. The proposed model is applied and tested on real data collected in the Republic of Serbia.