Eurasian Journal of Biosciences

Forecasting of the risks in the agro-industrial complex system


The agro-industrial complex system refers to complex heterogeneous systems often exposed to external and internal risks of various nature: environmental, economic, technical, technological, social and financial. The forecasting of riskogenic events and risk management in the agro-industrial complex system is characterized by imperfection of methodological and tool support. The methods of expert assessment and cognitive modeling are not used enough in the process of risk forecasting. There is a significant number of studies on risk forecasting in the agro-industrial complex, but in general, the level of coverage of risks in the system is insufficient. The algorithms for research and forecasting of risks and risk management in the agro-industrial complex system are presented in our work. Theoretical and practical aspects of the use of expert assessment methods, cognitive modeling, generation of scenarios for riskogenic situations based on a systemic analysis of potential situations are considered in risk forecasting. The algorithms we propose can be successfully applied in the context of digitalization of the agro-industrial complex for planning, monitoring and development of innovations in the technical, socio-economic and eco-economic subsystems of the agro-industrial complex.


  • Antonov, A.V. (2004). Systemic analysis. Vyssh Shk.
  • Blauberg, I.V. (1997). Integrity problem and systematic approach. Editorial URSS,
  • Bolbakov, R.G. (2015). “Foundations of Cognitive Management,” State Counselor, no. 1 (9), pp. 45-49,
  • Ivanyo, Ya.M.(2007). Extreme natural phenomena: methodology, modeling and forecasting. Irkutsk State Agricultural Academy.
  • Ivanyo, Y., Asalkhanov, P., Bendik, N. (2019). Management of the Agro-Industrial Enterprise: Optimization Uncertainty Expert Assessments International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2019
  • Khitrova, E., Khitrova, T. (2019). Information technology as a tool for improving banking supervision. AEBMR-Advances in Economics Business and Management Research. 81,312-316
  • Khitrova, T.I., Vlasov, A.N. (2014). “Methods and Technologies of Information Risk Management, Izvestia, Irkutsk State Economic Academy,” No. 3, p. 18.
  • Kononov, A.A., Kotelnikov, A.P. & Chernysh, K.V. (2012). “Assessment of the security of critical facilities based on the construction of risk event models,” Proceedings of the Institute for Systemic Analysis of the Russian Academy of Sciences, vol. 62, no. 4, pp. Ovanesyan, S.S. (2015). “Innovative method for calculating of the profitability of manufactured products,” Baikal research journal - V. 6, No. 6.
  • Krezhanovskaya, A.Yu. (2008). “Eco-economic risk factors in agriculture,” Terra Economicus, vol. 6, no. 4-4, pp. 128-129.
  • Kuzmenko, O.V. (2014). “Industrial Risk Management in Agriculture,” International Journal of Research, vol. 30, no. 11-3, pp. 45-47.
  • Lotov, A. V. (1989). Generalized reachable sets method in multiple criteria problems. In Methodology and Software for Interactive Decision Support (pp. 65-73). Springer, Berlin, Heidelberg.
  • Makarova, G.N. (2014). “State investment policy and strategic risks of Russia”, News of the Irkutsk State Economic Academy. № 1. P. 60-66.
  • Medvedev, N.A. (2016)."A Systemic Approach to Forecasting the Region's Agriculture: Mechanisms and Tools," Dairy Newsletter, no. 3 (23), pp. 100-110.
  • Medvedeva, N.A. (2016). Methodology of scenario forecasting of agricultural development in the regions of the European North of the Russian Federation: the dissertation ...of Doctor of Economics. FSBEI HPE Ural State Agricultural Academy.
  • Nalimov, V.V. & Ulchenko, Z.M. M. (1969). Naukometria. Studying of the science development as an information process. Nauka.
  • Nechaev, A., & Rasputina, A. (2020). Integrated depreciation management system. In IOP Conference Series: Earth and Environmental Science (Vol. 421). Institute of Physics Publishing.
  • Ovchinnikov, V.N. & Arshba, M.V. (2013). “Insurance as a method of managing risks arising from the negative impact of the external environment,” Terra Economicus, vol. 11, no. 3-3, pp. 5-9.
  • Peshina, E.V. & Sadykov, R.R. (2012). “On the classification of risks in the agro-industrial complex,” Regional Economics, no. 2, pp. 244-249.
  • Rasputina A, Zhilkina N, Ovanesyan S, & Tyunkov V. (2020). Prerequisites of State Regulation of Prices for Agricultural Products (through the Example of Poultry Farms in Siberia). International Session of Factors of Regional Extensive Development (FRED-2019). 01,113.
  • Rasputina, A., V; Ziboreva, O. Yu (2019). Cluster analysis as a tool for managing and forecasting target cost in poultry organizations AEBMR-Advances in Economics Business and Management Research. 81,331-335
  • Romanenko, I.A. & Evdokimova, N.E. (2018). “Modeling the adaptation of agriculture to long-term climate change,” Innovative, Information and Communication Technologies, no.1, pp.132-137.
  • Samarukha, A.V. (2014). “High-quality management of an industrial enterprise as the basis for the Siberian region to enter the path of industrial development,” Baikal research journalNo. 2.
  • Samarukha., V.I., Krasnova, T.G., Purdenko, Yu.A.(2006). “Corporate Governance,” Irkutsk: Publishing house of BSUEP, P. 8.
  • Samygin, D.Yu. Baryshnikov, N.G. & Mizyurkina, L.A. (2019). “Models of scenario forecasting for the development of agriculture in a region,” Regional Economics, vol. 15, no. 3, pp. 865-879.
  • Shannon, R. (1978). Imitation systems modeling - art and science. World.
  • Sukhodolov, A.P. & Marenko, V.A. (2018). Systemic analysis, modeling. Mathematical modeling. Publishing House of Baikal State University, 2018.
  • Sukhodolov A.P., Fedotov A.P., Anoshko P.N., Kolesnikova A.V., Sorokina P.G., Mamonova N.V.(2020). Mathematical modeling in researching the complex determinants of illegal fishing of water bio-resources (the omul fish) in Lake Baikal. Vserossiiskii kriminologicheskii zhurnal = Russian Journal of Criminology, vol. 14, no. 1, pp. 76–86. DOI: 10.17150/2500- 4255.2020.14(1).76-86. (In Russian).
  • Sukhodolov A.P., Fedotov A.P., Makarov М.М., Anoshko P.N., Gubiy E.V., Zorkaltsev V.I., Sorokina P.G., Mokry I.V., Lebedeva A.V.(2019) Mathematical modeling of assessing the number of Baikal omul in the system of socio-economic and legal aspects of environmental law violations. Russian Journal of Criminology, vol 13, no. 5, pp. 757–771. DOI: 10.17150/2500- 4255.2019.13(5).757-771. (In Russian).
  • Tyrsin, A.N. & Surina, A.A. (2017). “Risk modeling in multidimensional stochastic systems,” Bulletin of Tomsk State University. Management, computer engineering and informatics, no. 39, pp. 65-72.
  • Yakhneeva, I.V. (2013). Modeling and designing of supplies at risk. Biblio-Globus, 2013.


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