Forecasting rolling stock indicators in the market of transport services using the neural network method

Abstract

The research is aimed at identifying patterns in the formation of tariffs, forecasting wagon rental rates and other indicators of the use of rolling stock using the neural network method. The process of tariff formation in the transport services market is investigated using the neural network method on the 1C platform. Various indicators of wagon use that affect the wagon rental rate are presented. They consider various approaches to tariff setting and propose principles for an optimal approach to setting tariffs in modern conditions. The results of the research can be applied in the further development of methods for forecasting and setting tariffs in railway transport. Keywords. railway tariff, wagon, rolling stock indicators, mathematical analysis, neural network method, forecasting.