Tomasz Wołowiec – University of Economics and Innovation in Lublin, Projektowa str. 4, 20-209 Lublin, Poland
Volodymyr Martyniuk – University of Economics and Innovation in Lublin, Projektowa str. 4, 20-209 Lublin, Poland
DOI: https://doi.org/10.31410/ERAZ.2020.239
6th International Conference – ERAZ 2020 – KNOWLEDGE BASED SUSTAINABLE DEVELOPMENT, Online/virtual, May 21, 2020, CONFERENCE PROCEEDINGS
Published by: Association of Economists and Managers of the Balkans – Belgrade, Serbia
Conference partners: Faculty of Economics and Business, Mediterranean University, Montenegro; University of National and World Economy – Sofia, Bulgaria; Faculty of Commercial and Business Studies – Celje, Slovenia; Faculty of Applied Management, Economics and Finance – Belgrade, Serbia
ISSN 2683-5568, ISBN 978-86-80194-33-2, DOI: https://doi.org/10.31410/ERAZ.2020
Abstract
The possibility of using artificial radial basis function neural networks for modeling of economic
phenomena and processes is shown. The basic characteristics and parameters of an artificial
radial basis function neural network are shown and the advantages of using this type of artificial
neural networks for modeling economic phenomena and processes are emphasized. Using an artificial
radial basis function neural network, together with official statistics for 2010-2017, the modeling of the
influence caused by work efficiency indicators of the customs authorities of Ukraine on the indicators
of economic security of Ukraine was carried out. The results obtained showed good analytical and
prognostic properties of an artificial radial basis function neural network when modeling the impact of
customs authorities’ performance on the state’s economic security indicators.
Key words
Economic security of the state, Radial Basis Function Neural Networks, Customs system,
Indicators of economic security of the state, Macroeconomic forecasting.
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