Abstract
The economic importance of transport in the life of society is to ensure the development, communication and coordination of the work of all sectors of the economy. Transport contributes to the solidity of the state, allows you to maneuver resources, promptly resolve emergencies and coordinate issues related to the health of the nation. One of the most important indicators of social life in terms of the development of the transport system is the death rate on the roads. The models of forecasting the development of the transport system of the Russian Federation, based on a mathematical model of the spread of innovative technologies, on the example of rail and road transport, are considered. Generalizations of models and some results of their research are given. The article presents a comparative analysis of the Russian transport system by 11 indicators in accordance with the frequency of deaths in road accidents per 100,000 populations according to Rosstat data for 2020. Machine learning methods collected in the Data Master Azforus (DMA) program were applied. The conducted studies have demonstrated the effectiveness of using machine learning methods to identify patterns linking the number of deaths in road accidents per 100,000 populations with the indicators of the transport system.
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