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The article discusses a problem of the efficiency of the regenerative braking’s increase on the DC railway section. For the detection of the causes of the decrease of the specific regeneration’s level on the area an algorithm is offered, which enables to determine the causes of the decrease of the specific regeneration’s level on the arbitrary monitoring’s area in view of the determination of the locomotive’s capacity for work, work parameters of the electric traction system and the executed graphic time-table. In the article the main phases of the algorithm’s work were considered by the example of the one of the railway sections.

The quality of a track circuit monitoring system is defined to the great extent by its ability to automatically analyse the acquired data, i. e. identify the state of a track circuit. Machine learning techniques can be applied to implement this functionality. Designing a machine learning algorithm requires a learning data set from the subject domain. In this article we discuss a basic principle of track circuit mathematical model design that could be used to generate such data set. We also apply this principle and a combination of some existing methods to design and demonstrate a mathematical model of the 25 Hz AC track circuit.