Research on the Issue of Prognosticationing the Volume of Passenger Traffic on Railway Transport in Meanrn Conditions(Pages 236-245)
Tetiana V. Butko1,*, Hanna O. Prymachenko2, Anton O. Kovalov3, Kyrylo О. Tarasov2 and Alina V. Kolisnyk4
1Department of Operational Work Management Ukrainian State University of Railway Transport 61001, 7 Feuerbach Square, Kharkiv, Ukraine.
2Department of Transport Systems and Logistics Ukrainian State University of Railway Transport, 61001, 7 Feuerbach Square, Kharkiv, Ukraine.
3Department of Cargo and Commercial Work Management Ukrainian State University of Railway Transport 61001, 7 Feuerbach Square, Kharkiv, Ukraine.
4Department of Railway Stations and Units Ukrainian State University of Railway Transport 61001, 7 Feuerbach Square, Kharkiv, Ukraine.
Relevance of the research: The relevance of the study is due to the growing demand for passenger transportation in Ukraine and the countries of the European Union in the conditions of demand uncertainty and of the complexity of planning the work of railway operators. Given the fact that the railway transport system is quite inertial, including in the field of passenger transportation, a certain period of time is required for its timely restructuring, when certain factors affect it. The speed of adaptation to new conditions, as well as to their consequences, directly affect the quality of the system. That is why, to obtain the most optimal result, it is necessary to use the data obtained on the basis of prognostication. The purpose of the research: The purpose of the article is to analyze the factors influencing the predictive number of passengers to improve the processes of planning railway routes for the delivery of passengers due to the use of neural networks and minimizing the total cost of transportation. Approaches: Taking into account the specifics of the operation and management of passenger railway transportation is proposed an approach of using a software module based on neural networks as a decision support system regarding planned volumes of passenger traffic for railway operators of Ukraine and other countries. Results: The article presents the results of the software product based on neural networks for the analysis and theoretical generalization of the influence of various factors on the prognostication of passenger flows of transport systems of passenger service, supply chains involving railway transport. The significance of the results: The materials of the article are of practical value for the professional and industrial training of logistics operators, employees of transport companies for scientific and pedagogical workers in order to improve their professional competences.
Passenger flow, Railway transport, Neural network, Passenger transportation, Transport operator.
How to Cite:
Tetiana V. Butko, Hanna O. Prymachenko, Anton O. Kovalov, Kyrylo О. Tarasov and Alina V. Kolisnyk. Research on the Issue of Prognosticationing the Volume of Passenger Traffic on Railway Transport in Meanrn Conditions. [ref]: vol.21.2023. available at: https://refpress.org/ref-vol21-a22/
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