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Dynamic Bayesian Networks Application for Economy Competitiveness Situational Modelling

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Advances in Intelligent Systems and Computing V (CSIT 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1293))

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Abstract

In the research, a dynamic BN (DBN) was designed to assess general trends in the level of regional competitiveness depending on economic detectors. This dynamic model is built on the basis of a trained, already verified static Bayesian network for assessing the country’s competitiveness. In contradistinction to an approach based on entrance from a numerical model as an entrance to a static network to foretell the meanings ​​of key detectors, the presented DBN uses the observed meanings ​​of key detectors to foretell future meanings ​​of these detectors taking into account the time component. Sensitivity analysis of BN is carried out, as well as a comparative analysis of “what-if” taking into account time steps. During the development of this DBN, it was found that the more evidence there is, the higher the accuracy of the designed network. The study identified baseline conditions, under which the competition detector at subsequent time steps will tend to increase. It is shown that to achieve the maximum level of competitiveness, we need to ensure the pursuit of maximum investment and innovation performance and improve the overall economic situation of the country.

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Author information

Authors and Affiliations

  1. Kherson National Technical University, Kherson, Ukraine

    Mariia Voronenko, Nataliia Krugla, Elzara Topalova, Viktoriia Filippova & Volodymyr Lytvynenko

  2. National University of Water and Environmental Engineering, Rivne, Ukraine

    Dmytro Nikytenko & Nataliia Savina

  3. Jan Evangelista Purkyne University in Usti Nad Labem, Usti Nad Labem, Czech Republic

    Jan Krejci

  4. University of State Fiscal Service of Ukraine, Kiev, Ukraine

    Oleksandr Naumov

Authors
  1. Mariia Voronenko
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  2. Dmytro Nikytenko
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  3. Jan Krejci
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  4. Nataliia Krugla
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  5. Oleksandr Naumov
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  6. Nataliia Savina
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  7. Elzara Topalova
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  8. Viktoriia Filippova
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  9. Volodymyr Lytvynenko
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Correspondence to Mariia Voronenko .

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Editors and Affiliations

  1. Department of Artificial Intelligence, Lviv Polytechnic National University, Lviv, Ukraine

    Natalya Shakhovska

  2. Institute of Computer Science and Information Technologies, Lviv Polytechnic National University, Lviv, Ukraine

    Mykola O. Medykovskyy

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Voronenko, M. et al. (2021). Dynamic Bayesian Networks Application for Economy Competitiveness Situational Modelling. In: Shakhovska, N., Medykovskyy, M.O. (eds) Advances in Intelligent Systems and Computing V. CSIT 2020. Advances in Intelligent Systems and Computing, vol 1293. Springer, Cham. https://doi.org/10.1007/978-3-030-63270-0_14

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