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Methodological Basis of Causal Forecasting of the Economic Systems Development Management Processes Under the Uncertainty

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Lecture Notes in Computational Intelligence and Decision Making (ISDMCI 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1246))

Abstract

The methodological bases of information support of the contribution of economic development indicators for variables input are proposed. Structural diagrams, directions and quantitative estimates of the causal relationships of the factors affecting the output dependent variable are developed. It is suggested that the difference between apriori and aposteriori entropy of economic system indicators is to be taken as a measure of removing information uncertainty. To improve the accuracy of quantitative estimates of the likelihood of linkages between economic indicators and input variables, we propose to use the Bayes formula. The algorithm of causal prediction is presented. It is recommended to model the forecasting situations using Bayesian networks, which allow us to encode knowledge of causal and associative relationships to make management decisions for the development of complex economic systems.

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Author information

Authors and Affiliations

  1. Kherson National Technical University, Kherson, Ukraine

    Marharyta Sharko

  2. Lviv Polytechnic National University, Lviv, Ukraine

    Nestor Shpak

  3. Khmelnytsky National University, Khmelnytsky, Ukraine

    Olga Gonchar

  4. Limkokwing University of Creative Technology, Kuala Lumpur, Malaysia

    Kateryna Vorobyova

  5. Private Higher Education Institution International University of Business and Law, Kherson, Ukraine

    Olena Lepokhina

  6. International University of Business and Law, Kherson, Ukraine

    Juliya Burenko

Authors
  1. Marharyta Sharko
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  2. Nestor Shpak
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  3. Olga Gonchar
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  4. Kateryna Vorobyova
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  5. Olena Lepokhina
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  6. Juliya Burenko
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Corresponding author

Correspondence to Marharyta Sharko .

Editor information

Editors and Affiliations

  1. Department of Informatics, Jan Evangelista Purkyně University in Ústí nad Labem, Ústí nad Labem, Czech Republic

    Sergii Babichev

  2. Department of Informatics and Computer Science, Kherson National Technical University, Kherson, Ukraine

    Volodymyr Lytvynenko

  3. Institute of Electronics and Information, Lublin University of Technology, Lublin, Poland

    Waldemar Wójcik

  4. Department of Informatics and Computer Science, Kherson National Technical University, Kherson, Ukraine

    Svetlana Vyshemyrskaya

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Sharko, M., Shpak, N., Gonchar, O., Vorobyova, K., Lepokhina, O., Burenko, J. (2021). Methodological Basis of Causal Forecasting of the Economic Systems Development Management Processes Under the Uncertainty. In: Babichev, S., Lytvynenko, V., Wójcik, W., Vyshemyrskaya, S. (eds) Lecture Notes in Computational Intelligence and Decision Making. ISDMCI 2020. Advances in Intelligent Systems and Computing, vol 1246. Springer, Cham. https://doi.org/10.1007/978-3-030-54215-3_27

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