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The use of artificial neural networks when planning the target indicators for the truck haulage development in the Russian Federation

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  • Gavrilenko N. G.

    (Omsk Humanitarian Academy, Omsk, Russian Federation)

Abstract

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.

Suggested 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," Russian Journal of Social Sciences and Humanities, Omsk Humanitarian Academy, vol. 15(2), pages 213-218, June.
    • Handle: RePEc:aws:omskjl:v:15:y:2021:i:2:p:213-218
    DOI: 10.17238/issn1998-5320.2021.15.2.26
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    References listed on IDEAS

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    1. Lund, Henrik & Hvelplund, Frede, 2012. "The economic crisis and sustainable development: The design of job creation strategies by use of concrete institutional economics," Energy, Elsevier, vol. 43(1), pages 192-200.
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    More about this item

    Keywords

    road transport; planning; forecasting; artificial neural networks;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

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    Access and download statistics

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