N. G. Gavrilenko
Omsk Humanitarian Academy, Omsk, Russian Federation
The use of artificial neural networks when planning the target indicators for the truck haulage development in the Russian Federation
Annotation. Currently, the development of truck haulage is determined by the Transport Strategy of the Russian Federation for the period up to 2030, the implementation of which in the future is unlikely, including due to the insufficient efficiency of the target indicator planning system. Consequently, the task of choosing effective methods for planning indicators is of particular relevance. The research is based on a review of scientific literature, the study of strategic planning documents of the Russian Federation, comparison methods, logical and axiomatic methods. The article substantiates the need to form a digital control system for truck haulage with elements of artificial intelligence. It is shown that the use of artificial neural networks is preferable when planning target indicators of development. The “inputs” and “outputs” for training seven neural networks are presented, which allow obtaining the limiting values of the target indicators of the truck haulage in the RF. The possibility of training artificial neural networks with an acceptable level of error according to the data presented for further use in the digital control system of truck haulage in the Russian Federation has been proved using Neural Excel, an analytical add-on for Microsoft Exce.
Keywords: road transport, planning, forecasting, artificial neural networks.
Paper submitted: May 24, 2021.
For citation: Gavrilenko N. G. (2021). The use of artificial neural networks when planning the target indicators for the truck haulage development in the Russian Federation. The Science of Person: Humanitarian Researches, vol. 15, no. 2, pp. 213–218. DOI: 10.17238/issn1998-5320.2021.15.2.26.
