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In general, improvement of methods for electrical calculations aimed at increasing the accuracy of the results. One of the ways to improve the methods of calculation is the account in the calculation of the various factors that affect the accuracy of calculation of the traction power system parameters. This article describes an approach aimed at improving the method of calculation in the electrical part to improve the accuracy by changing the algorithm for calculating and accounting for a number of additional factors.

Nowadays fuzzy neural networks are widely used for modeling of complex industrial processes. The paper considers the application of fuzzy logic to generate a mathematical model of electricity consumption in rail transport for example, traction substation Dorogino. Algorithm for choice of the structure of fuzzy neural network including the species and number of membership functions for input and the number of training cycles is presented. Comparative analysis of the structures by evaluating the mean square error is made.