Cognitive Modeling in the Management of Economic Growth of the Agriculture in Russia
Abstract
The article analyzes the processes of economic growth in the agriculture in Russia. The current state of the agriculture, characterized by a variety of technological structures and various levels of economic and social development of enterprises and rural areas, has been considered. Tendencies of development and the reasons restraining the further growth of industry have been shown. The parametric content of management system of economic growth of agriculture has been determined on the basis of cognitive modeling. A fuzzy cognitive map for management of economic growth of the industrial complex has been developed, the static and dynamic analysis of which allowed obtaining forecasts of the dynamics of agriculture under various management influences. As a result, a strategy for achievement of the target parameters of the economic dynamics of the agricultural economy has been formed. A conclusion on the prospects for the development of the agriculture with an effective agrarian policy is drawn.
References
[1] Anokhina, M.Y. 2017a. Management of the agro-industrial complex economic growth. Moscow. Ankil publishing house.
[2] Anokhina, M.Y. (2017b). Strategy of managing growth of agricultural production in Russia. Journal of Experimental Biology and Agricultural Sciences, 5(6): 793 - 805. DOI: http://dx.doi.org/10.18006/2017.5(6).793.805
[3] Anokhina, M.Y., Zinchuk G.M., Petrovskaya S.A., and Butov A.V. 2018. Managing Competitiveness of Agro-industrial Production in Russia. Journal of Applied Economic Sciences, 1(55): 196 – 206.
[4] Atkin, R.H., and Casti, J. 1977. Polyhedral dynamics and the geometry of systems, RR-77-6. International institute for applied systems analysis. Laxenburg (Austria). March.
[5] Avdeeva, Z.K., Kovriga, S.V., and Makarenko, D.I. 2007. Cognitive modeling for solving problems in the management of weakly structured systems (situations). Management of large systems, 16: 26–39.
[6] Axelrod, R. 1976. The Structure of Decision: Cognitive Maps of Political Elites. Princeton, NJ: Prinston University Press.
[7] Borisov, V.V., Kruglov, V.V., and Fedulov, A.S. 2007. Fuzzy models and networks. Moscow. Hot line - Telecom.
[8] Casti, J. 1982. Connectivity, complexity, and catastrophe in large-scale systems. Moscow. Mir publishing house.
[9] Erokhin, D. V., Lagerev, D. G., Laricheva, E. A., and Podvesovskii, A.G. 2010. Strategic management of innovative activity of the enterprise. Bryansk. BSTU.
[10] GKS. The official website of the Federal State Statistics Service of the Russian Federation. Available at: http://www.gks.ru/.
[11] Golubev, A. V. 2010. Scientific bases of innovative development of agriculture. APC: Economics, management, 10: 30-35.
[12] Golubev, A. V. 2012. Paradoxes of development of the agrarian economy of Russia. Voprosy Economiki, 1: 115-126.
[13] Gorelov, V.I., Karelova, O.L., and Ledashcheva, T.N. 2012. System modeling in socio-economic sphere. Moscow. Logos.
[14] Isaev, R.A., and Podvesovskii, A.G. 2017. Generalized Model of Pulse Process for Dynamic Analysis of Sylov’s Fuzzy Cognitive Maps. CEUR Workshop Proceedings of the Mathematical Modeling Session at the International Conference Information Technology and Nanotechnology (MM-ITNT 2017). Vol. 1904: 57-63. Doi: 10.18287/1613-0073-2017-1904-57-63.
[15] Kolodenkova, A.E. 2017. Methods of decision support in the analysis of the feasibility of projects for information and management systems of industrial facilities. Dissertation of Doctor of Technical Sciences, Ufa State Aviation Technical University.
[16] Kopeliovich, D. I., et al. 2018. Application of Fuzzy Cognitive Models in Computer - Aided Production Tooling Design. Herald of Computer and Information Technologies, 3: 20-35.
[17] Kosko, B. 1986. Fuzzy cognitive maps. International Journal of Man-Mashine Studies, 24(1): 65-75.
[18] Krioni, N.K., Kolodenkova, A.E., Korobkin, V.V., and Gubanov, N.G. (2016). Intelligent decision-making support system using cognitive modeling for project feasibility assessment on creating complex technical. International Journal of Applied Business and Economic Research, 14 (10): 7289–7300.
[19] Kruglov, V.V. and Dli, M.I. 2002. Intellectual information systems: computer support of fuzzy logic and fuzzy inference. Textbook. Moscow. Fizmatlit.
[20] Kulinich, A.A. 2010. Computer systems for modeling cognitive maps: approaches and methods. Problems of management, 3: 2-16.
[21] Maksimov, V.I. 2001. Cognitive technologies – from ignorance to understanding. Cognitive analysis and management of the development of situations (СASC). Collection of works of the 1st International Conference. Moscow. Institute of Control Sciences of the Russian Academy of Sciences,1: 4–18.
[22] Podvesovskii, A. G., Lagerev, D. G., and Korostelyov, D. A. 2009. Application of Fuzzy Cognitive Models for Construction of Alternatives Set in Decision Problems. Bulletin of Bryansk State Technical University, 24: 77-84.
[23] Roberts, F. 1978. Graph Theory and its applications to problems of society, society for industrial and applied mathematics. Philadelphia. Society for Industrial and Applied Mathematics.
[24] Silov, V.B. 1995. Making strategic decisions in fuzzy environment. Moscow. INPRO-ROS.
[25] SSDS "IGLA". The software system of decision support “Intelligent Generator of the Best Alternatives”. Developed in Bryansk State Technical University under the supervision of Podvesovskii A.G. Available at: http://iipo.tu-bryansk.ru/quill/download.html
[26] The World Bank. Available at: http://www.worldbank.org/en/country/russia/publication/policies-for-agri-food-sector-competitiveness-and-investment
[2] Anokhina, M.Y. (2017b). Strategy of managing growth of agricultural production in Russia. Journal of Experimental Biology and Agricultural Sciences, 5(6): 793 - 805. DOI: http://dx.doi.org/10.18006/2017.5(6).793.805
[3] Anokhina, M.Y., Zinchuk G.M., Petrovskaya S.A., and Butov A.V. 2018. Managing Competitiveness of Agro-industrial Production in Russia. Journal of Applied Economic Sciences, 1(55): 196 – 206.
[4] Atkin, R.H., and Casti, J. 1977. Polyhedral dynamics and the geometry of systems, RR-77-6. International institute for applied systems analysis. Laxenburg (Austria). March.
[5] Avdeeva, Z.K., Kovriga, S.V., and Makarenko, D.I. 2007. Cognitive modeling for solving problems in the management of weakly structured systems (situations). Management of large systems, 16: 26–39.
[6] Axelrod, R. 1976. The Structure of Decision: Cognitive Maps of Political Elites. Princeton, NJ: Prinston University Press.
[7] Borisov, V.V., Kruglov, V.V., and Fedulov, A.S. 2007. Fuzzy models and networks. Moscow. Hot line - Telecom.
[8] Casti, J. 1982. Connectivity, complexity, and catastrophe in large-scale systems. Moscow. Mir publishing house.
[9] Erokhin, D. V., Lagerev, D. G., Laricheva, E. A., and Podvesovskii, A.G. 2010. Strategic management of innovative activity of the enterprise. Bryansk. BSTU.
[10] GKS. The official website of the Federal State Statistics Service of the Russian Federation. Available at: http://www.gks.ru/.
[11] Golubev, A. V. 2010. Scientific bases of innovative development of agriculture. APC: Economics, management, 10: 30-35.
[12] Golubev, A. V. 2012. Paradoxes of development of the agrarian economy of Russia. Voprosy Economiki, 1: 115-126.
[13] Gorelov, V.I., Karelova, O.L., and Ledashcheva, T.N. 2012. System modeling in socio-economic sphere. Moscow. Logos.
[14] Isaev, R.A., and Podvesovskii, A.G. 2017. Generalized Model of Pulse Process for Dynamic Analysis of Sylov’s Fuzzy Cognitive Maps. CEUR Workshop Proceedings of the Mathematical Modeling Session at the International Conference Information Technology and Nanotechnology (MM-ITNT 2017). Vol. 1904: 57-63. Doi: 10.18287/1613-0073-2017-1904-57-63.
[15] Kolodenkova, A.E. 2017. Methods of decision support in the analysis of the feasibility of projects for information and management systems of industrial facilities. Dissertation of Doctor of Technical Sciences, Ufa State Aviation Technical University.
[16] Kopeliovich, D. I., et al. 2018. Application of Fuzzy Cognitive Models in Computer - Aided Production Tooling Design. Herald of Computer and Information Technologies, 3: 20-35.
[17] Kosko, B. 1986. Fuzzy cognitive maps. International Journal of Man-Mashine Studies, 24(1): 65-75.
[18] Krioni, N.K., Kolodenkova, A.E., Korobkin, V.V., and Gubanov, N.G. (2016). Intelligent decision-making support system using cognitive modeling for project feasibility assessment on creating complex technical. International Journal of Applied Business and Economic Research, 14 (10): 7289–7300.
[19] Kruglov, V.V. and Dli, M.I. 2002. Intellectual information systems: computer support of fuzzy logic and fuzzy inference. Textbook. Moscow. Fizmatlit.
[20] Kulinich, A.A. 2010. Computer systems for modeling cognitive maps: approaches and methods. Problems of management, 3: 2-16.
[21] Maksimov, V.I. 2001. Cognitive technologies – from ignorance to understanding. Cognitive analysis and management of the development of situations (СASC). Collection of works of the 1st International Conference. Moscow. Institute of Control Sciences of the Russian Academy of Sciences,1: 4–18.
[22] Podvesovskii, A. G., Lagerev, D. G., and Korostelyov, D. A. 2009. Application of Fuzzy Cognitive Models for Construction of Alternatives Set in Decision Problems. Bulletin of Bryansk State Technical University, 24: 77-84.
[23] Roberts, F. 1978. Graph Theory and its applications to problems of society, society for industrial and applied mathematics. Philadelphia. Society for Industrial and Applied Mathematics.
[24] Silov, V.B. 1995. Making strategic decisions in fuzzy environment. Moscow. INPRO-ROS.
[25] SSDS "IGLA". The software system of decision support “Intelligent Generator of the Best Alternatives”. Developed in Bryansk State Technical University under the supervision of Podvesovskii A.G. Available at: http://iipo.tu-bryansk.ru/quill/download.html
[26] The World Bank. Available at: http://www.worldbank.org/en/country/russia/publication/policies-for-agri-food-sector-competitiveness-and-investment
Published
2019-05-08
How to Cite
ANOKHINA, Marina Y.; GOLUBEV, Alexey V.; KONDRASHINA, Olga N..
Cognitive Modeling in the Management of Economic Growth of the Agriculture in Russia.
Journal of Environmental Management and Tourism, [S.l.], v. 10, n. 1, p. 119-134, may 2019.
ISSN 2068-7729.
Available at: <https://journals.aserspublishing.eu/jemt/article/view/3196>. Date accessed: 08 may 2024.
doi: https://doi.org/10.14505//jemt.v10.1(33).12.
Section
Article
Copyright© 2023 The Author(s). Published by ASERS Publishing 2023. This is an open access article distributed under the terms of CC-BY 4.0 license.