Matematicheskoe modelirovanie
RUS  ENG    JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB  
General information
Latest issue
Archive
Impact factor

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS



Mat. Model.:
Year:
Volume:
Issue:
Page:
Find






Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register


Matematicheskoe modelirovanie, 2016, Volume 28, Number 7, Pages 96–106 (Mi mm3751)  

This article is cited in 56 scientific papers (total in 56 papers)

Optimal control of sustainable development in biological rehabilitation of the Azov Sea

A. Nikitinaa, A. I. Sukhinovb, G. A. Ugolnitskya, A. B. Usova, A. E. Chistyakova, M. Puchkina, I. S. Semenova

a Southern Federal University
b Don State Technical University
References:
Abstract: The article is devoted to the application of the concept of sustainable development management to the task of combating the eutrophication of shallow water (on the example of the Azov Sea). When describing the state dynamics of the reservoir are PDEs that are solved numerically by a finite difference method. Dynamic problem of minimizing the cost of ecosystem maintaining of the reservoir in defined condition, which is interpreted as the requirement of sustainable development, is solved. Research and forecast complex was developed, which include mathematical models of hydrobiology of shallow water, a database of environmental data, and program library, used to design of development scenarios of ecological condition in the Azov Sea. The forecast of changes of concentration of malicious blue-green algae due to water pollution of shallow water by nutrients, which are caused rapid growth of these algae, was given. The influence of the spatial distribution of temperature, salinity on biological treatment of the Azov Sea through the introduction of green algaes, displaced toxic blue-green algaes. Using deigned research and forecast complex that is used the materials of expedition works, we can study the key mechanisms of formation of horizontal and vertical zones in the distribution of concentrations of nutrients, oxygen and plankton populations, to set the values of parameters control the amount of hydrogen sulfide and hypoxemic zones, to evaluate the possibility of biological treatment of the waters of the Azov Sea with the help of his introduction green algae Chlorella vulgaris BIN, followed by displacement of toxic most common in shallow waters the blue-green algae, such as Aphanizomenon flos-aquae, to rank eco-efficiency control factors the stability of the species composition of phytoplankton, including " algal bloom" of microalgae. Examples of numerical calculations and the analysis of the obtained results were given.
Keywords: optimal control, simulation, homeostasis, algae, grid, discrete model.
Funding agency Grant number
Southern Federal University 213.01-07-2014/07ПЧВГ
Received: 26.03.2015
English version:
Mathematical Models and Computer Simulations, 2017, Volume 9, Issue 1, Pages 101–107
DOI: https://doi.org/10.1134/S2070048217010112
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: A. Nikitina, A. I. Sukhinov, G. A. Ugolnitsky, A. B. Usov, A. E. Chistyakov, M. Puchkin, I. S. Semenov, “Optimal control of sustainable development in biological rehabilitation of the Azov Sea”, Mat. Model., 28:7 (2016), 96–106; Math. Models Comput. Simul., 9:1 (2017), 101–107
Citation in format AMSBIB
\Bibitem{NikSukUgo16}
\by A.~Nikitina, A.~I.~Sukhinov, G.~A.~Ugolnitsky, A.~B.~Usov, A.~E.~Chistyakov, M.~Puchkin, I.~S.~Semenov
\paper Optimal control of sustainable development in biological rehabilitation of the Azov Sea
\jour Mat. Model.
\yr 2016
\vol 28
\issue 7
\pages 96--106
\mathnet{http://mi.mathnet.ru/mm3751}
\elib{https://elibrary.ru/item.asp?id=26604119}
\transl
\jour Math. Models Comput. Simul.
\yr 2017
\vol 9
\issue 1
\pages 101--107
\crossref{https://doi.org/10.1134/S2070048217010112}
\scopus{https://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-85012024693}
Linking options:
  • https://www.mathnet.ru/eng/mm3751
  • https://www.mathnet.ru/eng/mm/v28/i7/p96
  • This publication is cited in the following 56 articles:
    1. A. Yu. Perevaryukha, “Computational Modeling of Transformations of Epidemic Waves of BA.2.86/JN.1 SAR-COV-2 Coronavirus Variants on the Basis of Hybrid Oscillators”, Tech. Phys., 2024  crossref
    2. A. Yu. Perevaryukha, “Improving the Method for Simulating the Evolution of SAR-CoV-2 in the Form of Hybrid SIR Models for Predicting New COVID-19 Waves”, Tech. Phys. Lett., 2024  crossref
    3. A. Yu. Perevaryukha, “Computational Modeling of the Scenario of Resumption of Covid-19 Waves under Pulse Evolution in New Omicron Lines”, Tech. Phys. Lett., 2024  crossref
    4. A. Yu. Perevaryukha, “Correspondence to biophysical criteria of nonlinear effects in the occurrence of Feigenbaum  bifurcation cascade in models of invasive processes”, CMIT, 6:1 (2023), 41  crossref
    5. E. A. Protsenko, N. D. Panasenko, A. V. Strazhko, “Original article Spatial-three-dimensional wave processes' modeling in shallow water bodies taking into account the vertical turbulent exchange features”, CMIT, 6:1 (2023), 34  crossref
    6. A. Yu. Perevaryukha, “Computational Modeling of Two Scenarios of Extreme Development of Biophysical Processes under a Regulated Control Strategy”, Tech. Phys., 67:9 (2022), 661  crossref
    7. I. V. Trofimova, A. Y. Perevaryukha, A. B. Manvelova, “Adequacy of Interpretation of Monitoring Data on Biophysical Processes in Terms of the Theory of Bifurcations and Chaotic Dynamics”, Tech. Phys. Lett., 48:12 (2022), 305  crossref
    8. T. Yu. Borisova, A. Yu. Perevaryukha, “On the Physicochemical Method of Analysis of the Formation of Secondary Immunodeficiency as a Bioindicator of the State of Ecosystems Using the Example of Seabed Biota of the Caspian Sea”, Tech. Phys. Lett., 48:7 (2022), 251  crossref
    9. A. Y. Perevaryukha, “Sriteria for Adequacy of the Cascade of Feigenbaum Bifurcations and Cycles of the Sharkovsky Ordering in Models of Transformable Biophysical Processes”, Tech. Phys., 67:12 (2022), 755  crossref
    10. A. Perevaryukha, “Dynamic model of population invasion with depression effect”, Informatics and Automation, 21:3 (2022), 604–623  mathnet  mathnet  crossref
    11. A. Yu. Perevaryukha, “Scenario of the invasive process in the modification of Bazykins population equation with delayed regulation and high reproductive potential”, Vestnik KRAUNC. Fiz.-Mat. Nauki, 39:2 (2022), 91–102  mathnet  mathnet  crossref
    12. S. A. Soldatenko, R. M. Yusupov, “On Scenarios of Changing the Optical Properties of the Atmosphere by Aerosol Injection for Climate Stabilization”, Opt. Spectrosc., 130:9 (2022), 540  crossref
    13. A. Y. Perevaryukha, “Modeling of a Crisis in the Biophysical Process by the Method of Predicative Hybrid Structures”, Tech. Phys., 67:6 (2022), 523  crossref
    14. A. Y. Perevaryukha, “Scenario modeling of the king crab stock collapse under expert control of annual catch”, Math. Models Comput. Simul., 14:6 (2022), 889–899  mathnet  crossref  crossref
    15. V. V. Mikhailov, A. Y. Perevaryukha, I. V. Trofimova, “Computational Modeling of the Nonlinear Metabolism Rate as a Trigger Mechanism of Extreme Dynamics of Invasion Processes”, Tech. Phys. Lett., 48:12 (2022), 301  crossref
    16. A. Yu. Perevaryukha, “Mathematical Modeling of Changes in the Growth Rate at the Early Stages of Development of Organisms for Biological Species with Metamorphosis in Ontogenesis”, Tech. Phys., 67:9 (2022), 651  crossref
    17. A. Yu. Perevaryukha, “Hybrid Model of the Collapse of the Commercial Crab Paralithodes camtschaticus (Decapoda, Lithodidae) Population of the Kodiak Archipelago”, BIOPHYSICS, 67:2 (2022), 300  crossref
    18. A I Sukhinov, A E Chistyakov, E A Protsenko, S V Protsenko, “Coastal protection structures influence on diffraction and reflection of waves simulation based on 3D wave hydrodynamics model”, J. Phys.: Conf. Ser., 1902:1 (2021), 012133  crossref
    19. Y V Belova, A E Chistyakov, A L Leontyev, A A Filina, A V Nikitina, “Mathematical modeling of phytoplankton populations evolution in the Azov Sea”, J. Phys.: Conf. Ser., 1745:1 (2021), 012118  crossref
    20. A L Leontyev, M I Chumak, A V Nikitina, I V Chumak, “Application of FPGA technologies for modeling hydrophysical processes in reservoirs with complex bottom topography”, IOP Conf. Ser.: Mater. Sci. Eng., 1029:1 (2021), 012076  crossref
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Математическое моделирование
    Statistics & downloads:
    Abstract page:579
    Full-text PDF :180
    References:75
    First page:15
     
      Contact us:
     Terms of Use  Registration to the website  Logotypes © Steklov Mathematical Institute RAS, 2025