DOI
10.34229/KCA2522-9664.25.6.7
UDC 517.9
K.L. Atoyev
V.M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine,
Kyiv, Ukraine,
konstantin_atoyev@yahoo.com
P.S. Knopov
V.M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine,
Kyiv, Ukraine,
knopov1@yahoo.com
MATHEMATICAL MODELING OF INSTABILITY IN ECOLOGICAL
AND ECONOMIC SYSTEMS
Abstract. The study of the mechanisms underlying the instability of complex ecological-economic systems was conducted to identify effective strategies for managing the energy sector of the economy in the context of climate change. The work uses a six-sector Lorenz model with variable coefficients, which combines in a single structure the sectors of the economy described in the same way, each of which is considered in terms of productivity levels, the number of jobs, and structural violations. The model allows us to investigate how changes in the ratio of demand and supply in individual industries and the speed of eliminating violations in the ecological-economic systems affect the share of green energy in the energy balance, the total volume of greenhouse gas emissions and energy production, and the number of structural disturbances in all sectors of the economy. The conditions for the occurrence of instability in complex ecological-economic systems associated with turbulent regimes, which lead to an increase in the total number of structural disturbances and a decrease in the overall level of productivity, are determined.
Keywords: Lorenz model, mathematical modeling, model of economic development, optimal сontrol, deterministic chaos, climate changes.
full text
REFERENCES
- 1. Laszlo E. Age of bifurcation: Understanding the changing world. Philadelphia; London: Gordon & Breach Science Publishers, 1991. 126 p.
- 2. Kroger W., Zio E. Vulnerable systems. London: Springer, 2011. XIV, 204 p. https://doi.org/10.1007/978-0-85729-655-9.
- 3. Ermoliev Yu., von Winterfeldt D. Systemic risk and security management. In: Managing Safety of Heterogeneous Systems. Ermoliev Yu., Makowski M., Marti K. (Eds.). LNE. 2012. Vol. 658. P. 19–49. https://doi.org/10.1007/978-3-642-22884-1.
- 4. Wilkinson A., Elahi S., Eidinow E. Section 3. Riskworld scenarios. Journal of Risk Research. 2003. Vol. 6, Iss. 4–6. P. 297–334. https://doi.org/10.1080/1366987032000109249.
- 5. Atoyev K., Knopov P., Pepeliaev V., Kisala P., Romaniuk R., Kalimoldayev M. The mathematical problems of complex systems investigation under uncertainties. In: Recent Advanced in Information Technology. Wojcik W., Sikora J. (Eds.). London: CRC Press Taylor Francis Group, 2017. P. 135–171. http://dx.doi.org/10.1201/9781351243179-6.
- 6. Atoyev K.L., Knopov P.S. Application of robust methods for estimation of distribution parameters with a priori constraints on parameters in economics and engineering. Cybernetics and Systems Analysis. 2022. Vol. 58, N 5. P. 713–720. https://doi.org/10.1007/s10559-022-00504-8.
- 7. Atoyev K.L., Knopov P.S. Mathematical modeling of climate change impact on relationships of economic sectors. Cybernetics and Systems Analysis. 2023. Vol. 59, N 4. P. 535–545. https://doi.org/10.1007/s10559-023-00589-9.
- 8. Atoyev K.L., Knopov P.S. Mathematical model of risk assessment for critical infrastructure. Cybernetics and Systems Analysis. 2025. Vol. 61, N 2. P. 198–211. https://doi.org/10.1007/s10559-025-00760-4.
- 9. Lorenz E.N. Deterministic nonperiodic flow. Journal of the Atmospheric Sciences. 1963. Vol. 20, Iss. 2. P. 130–141. https://doi.org/10.1175/1520-0469(1963)020й:DNF2.0.CO;2.
- 10. Kaplan J.L., Yorke J.A. Preturbulence: A regime observed in a fluid flow model of Lorenz. Comm. Math. Phys. 1979. Vol. 67, Iss. 2. P. 93–108. https://doi.org/10.1007/BF01221359.
- 11. Zang W.-B. Synergetic economics: Time and change in nonlinear economics. Springer Series in Synergetics. Vol. 53. Berlin; Heidelberg: Springer-Verlag, 1991. 246 p. https://doi.org/10.1007/978-3-642-75909-3.
- 12. Magnitskii N.A., Sidorov S.V. New methods for chaotic dynamics. Singapore: World Scientific, 2006. 363 p.
- 13. Магницкий Ю.Н. Исследование зависимости макроэкономических показателей от структуры рыночной экономики. Труды ИСА РАН. 2005. Т. 14. С. 198–205.
- 14. Yang X.-S. An economy can have a Lorenz-type chaotic attractor. International Journal of Bifurcation and Chaos. 2021. Vol. 31, N 14. Article number 2150210. https://doi.org/10.1142/S0218127421502102.
- 15. Galizia D. Saddle cycles: Solving rational expectations models featuring limit cycles (or chaos) using perturbation method. Quantitative Economics. 2021. Vol. 12, N. 3. P. 869–901. https://doi.org/10.3982/QE1491.
- 16. Statistical yearbook of Ukraine 2022. Kyiv: State Statistics Service of Ukraine, 2023. 453 p. URL: https://ukrstat.gov.ua/druk/publicat/kat_u/2023/zb/11/year_22_e.pdf.
- 17. Agriculture of Ukraine 2022. Statistical collection. Kyiv: State Statistics Service of Ukraine, 2023. URL: https://ukrstat.gov.ua/druk/publicat/kat_u/2023/zb/09/S_gos_22.pdf.
- 18. Golodnikov A.N., Ermoliev Yu.M., Knopov P.S. Estimating reliability parameters under insufficient information. Cybernetics and Systems Analysis. 2010. Vol. 46, N 3. P. 443–459. https://doi.org/10.1007/s10559-010-9219-9.
- 19. Golodnikov A.N., Ermol’ev Yu.M., Ermol’eva T.Yu., Knopov P.S., Pepelyaev V.A. Integrated modeling of food security management in Ukraine. I. Model for management of the economic availability of food. Cybernetics and Systems Analysis. 2013. Vol. 49, N 1. P. 26–35. https://doi.org/10.1007/s10559-013-9481-8.
- 20. Golodnikov A.N., Ermol’ev Yu.M., Ermol’eva T.Yu., Knopov P.S., Pepelyaev V.A. Integrated modeling of food security management in Ukraine. II. Models for structural optimization of agricultural production under risk. Cybernetics and Systems Analysis. 2013. Vol. 49, N 2. P. 217–228. https://doi.org/10.1007/s10559-013-9503-6.
- 21. Ermoliev Yu.M., Zagorodny A.G., Bogdanov V.I., Ermolieva T.Yu, Havlik P., Obersteiner M., Rovenskaya E. Linking distributed sectorial optimization models under asymmetric information: towards robust food-water-environmental nexus. In: FEW Nexux for Sustainable Development: Integrated Modeling & Robust Management. Ermoliev Yu., Zagorodny A., Bogdanov V., Ermolieva T., Kostyuchenko Yu. (Eds.). Kyiv: Akademperiodika, 2020. P. 303–322. URL: https://www.calameo.com/read/0031683726252f5034d74.
- 22. Pepelyaev V.A., Golodnikov A.N., Golodnikova N.A. Reviewing climate changes modeling methods. Cybernetics and Systems Analysis. 2023. Vol. 59, N 3. P. 398–406. https://doi.org/10.1007/s10559-023-00574-2.
- 23. Pepelyaev V.A., Golodnikov A.N., Golodnikova N.A. Modeling the impact of climate change on the crop yield. Cybernetics and Systems Analysis. 2023. Vol. 59, N 6. P. 949–955. https://doi.org/10.1007/s10559-023-00631-w.
- 24. Pepelyaev V.A., Golodnikov A.N., Golodnikova N.A. Method of optimizing the structure of sowing areas for the adaptation of crop production to climate changes. Cybernetics and Systems Analysis. 2024. Vol. 60, N 3. P. 415–421. https://doi.org/10.1007/s10559-024-00682-7.
- 25. Shulzhenko S., Nechaieva T., Leshchenko I. The application of the optimal unit commitment problem for the studies of the national power sector development under system risks. In: Nexus of Sustainability. Zagorodny A. Bogdanov V., Zaporozhets A. (Eds.). SSDC. 2024. Vol. 559. P. 147–164. https://doi.org/10.1007/978-3-031-66764-0_7.