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Journal Nonlinear World №4 for 2022 г.
Article in number:
Design and research of population dynamic model "two competitors – two migration areas"
Type of article: scientific article
DOI: https://doi.org/10.18127/j20700970-202204-06
UDC: 517.9, 004.8, 519.6
Authors:

I.I. Vasilyeva1, O.V. Druzhinina2, O.N. Masina3

1, 3 Bunin Yelets State University (Yelets, Russia)

2 FRС «Computer Science and Control» of RAS (Moscow, Russia)

Abstract:

The analysis and synthesis of multidimensional dynamic population models belonging to the type "two competitors – two migration areas" are relevant problems. Important aspects of the study of such models are to clarify the nature of the trajectories, the transition to a stationary mode and the identification of new qualitative effects.

The purpose of this article is to construct and study a four-dimensional nonlinear population model with migration flows taking into account competition, to find out the influence of variability of coefficients of natural reproduction of species on the behavior of the system.

The population model "two competitors – two migration areas" is synthesized. The modeling of the processes of interaction of species in the conditions of competition and migration flows is carried out. A series of computer experiments are performed, projections of phase portraits are constructed, qualitative effects are identified and a comparative analysis of the results obtained for such a modification of the model "two competitors – two migration areas", which is associated with the variability of the coefficients of natural reproduction of species.

The results can be used in solving nonlinear dynamics problems related to modeling environmental, physical and chemical processes.

Pages: 60-68
For citation

Vasilyeva I.I., Druzhinina O.V., Masina O.N. Design and research of population dynamic model "two competitors – two migration areas". Nonlinear World. 2022. V. 20. № 4. 2022. P. 60-68. DOI: https://doi.org/10.18127/j20700970-202204-06 (In Russian)

References
  1. Bazykin A.D. Nelinejnaja dinamika vzaimodejstvujushhih populjacij. M.–Izhevsk: Institut komp'juternyh issledovanij. 2003.
  2. Aleksandrov A.Ju., Platonov A.V., Starkov V.N., Stepenko N.A. Matematicheskoe modelirovanie i issledovanie ustojchivosti biologicheskih soobshhestv. SPb.: Lan'. 2017 (In Russian).
  3. Riznichenko G.Ju. Matematicheskoe modelirovanie biologicheskih processov. Modeli v biofizike i jekologii. M.: Jurajt. 2020 (In Russian).
  4. Svirezhev Ju.M., Logofet D.O. Ustojchivost' biologicheskih soobshhestv. M.: Nauka. 1978 (In Russian).
  5. Gimel'farb A.A., Ginzburg L.R., Polujektov R.A., Pyh Ju.A., Ratner V.A. Dinamicheskaja teorija biologicheskih populjacij.
    M.: Nauka. 1974 (In Russian).
  6. Dilao R. Mathematical models in population dynamics and ecology. In book: Biomathematics: Modelling and simulation.
    Ed. J. C. Misra. Singapore: World Scientific. 2006. P. 399–449 (In Russian).
  7. Zhang X.-a., Chen L. The linear and nonlinear diffusion of the competitive Lotka–Volterra model. Nonlinear Analysis. 2007. V. 66. P. 2767–2776 (In Russian).
  8. Druzhinina O.V., Masina O.N. Metody analiza ustojchivosti dinamicheskih sistem intellektnogo upravlenija. M.: Izd. gruppa URSS. 2016.
  9. Druzhinina O.V., Masina O.N., Tarova E.D. Analiz i sintez nelinejnyh mnogomernyh dinamicheskih modelej s uchetom migracionnyh potokov i upravljajushhih vozdejstvij. Nelinejnyj mir. 2019. T. 17. № 5. S.24–37 (In Russian).
  10. Demidova А.V., Druzhinina О.V., Masina O.N., Tarova E.D. Computer research of nonlinear stochastic models with migration flows. CEUR Workshop Proceedings. 2019. V. 2407. P. 26–37.
  11. Druzhinina O.V., Masina O.N., Tarova E.D. Sintez, komp'juternoe issledovanie i analiz ustojchivosti mnogomernyh modelej dinamiki vzaimosvjazannyh soobshhestv. Nelinejnyj mir. 2019. T. 17. № 2. S. 48–58 (In Russian).
  12. Petrov A.A., Druzhinina O.V., Masina O.N., Vasil'eva I.I. Postroenie i analiz chetyrehmernyh modelej dinamiki populjacij s uchetom migracionnyh potokov. Uchenye zapiski UlGU. Ser. Matematika i informacionnye tehnologii. UlGU. Jelektronnyj zhurnal. 2022. № 1. S. 43–55 (In Russian).
  13. Karpenko A.P. Sovremennye algoritmy poiskovoj optimizacii. M.: MGTU im. N.Je. Baumana. 2017.
  14. Masina O.N., Petrov A.A., Druzhinina O.V., Rapoport L.B. Modelirovanie upravljaemyh sistem s primeneniem metodov stabilizacii i algoritmov poiska optimal'nyh traektorij. Elec: Eleckij gosudarstvennyj universitet im. I.A. Bunina. 2021.
  15. Sajmon D. Algoritmy jevoljucionnoj optimizacii. M.: DMK Press. 2020.
Date of receipt: 07.10.2022
Approved after review: 19.10.2022
Accepted for publication: 27.10.2022