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ESTIMATION OF FINAL DISTRIBUTION OF PROBABILITIES OF THREATS REALIZATION IN THE SPHERE OF ECONOMIC SECURITY BASED ON SIMULATION MODELING

https://doi.org/10.24412/2225-8264-2021-1-67-75

Abstract

An approach to assessing the probabilities of threats realization based on Markov random process is proposed in the article. In the system of indicators characterizing a certain area of economic safety, a stable state is distinguished, in which the values of all indicators are within the acceptable values, and several unstable states, in which some of the indicators are beyond the acceptable values. Transitions of the system between states are supposed under the influence of a certain set of threats to economic security in the form of an inhomogeneous Markov process. A feature of the model is that the rates of the transitions depends on the quantity of budgetary funds allocated by the structures responsible for monitoring the level of economic security, on eliminating potential threats or to weaken their action. It's shown that under certain constraints on the parameters of the model, a stationary regime is setting in the system, in which the probabilities of the system states don't depend on time. An algorithm for modeling the process of changing the states of the system at some finite time interval and calculating the final probabilities of states is described, based on the Monte Carlo method. A modeling program has been developed and the simplest example is given when budget funds are allocated in equal parts at regular intervals, regardless of the system state. It's shown that the results of imitation modeling are coincided with the analytical final distribution obtained from the Kolmogorov equations. The model and its program implementation can be useful tool for regional authorities dealing with the problems of monitoring economic safety and scenario forecasting of the socio-economic development of the region.

About the Authors

K. K. Loginov
Omsk scientific center of the SB RAS
Russian Federation

Konstantin K. Loginov



V. V. Karpov
Omsk scientific center of the SB RAS
Russian Federation

Valery V. Karpov



A. A. Korableva
Omsk scientific center of the SB RAS
Russian Federation

Anna A. Korableva



References

1. Afanasievsky L. B., Gorin A. N., Chursin M. A. Imitatsionnoe modelirovanie polumarkovskikh protsessov v sistemakh s diskretnymi sostoyaniyami i nepreryvnym vremenem [Imitation modeling of semi-markov processes in systems with discrete states and continuous time]. Vestnik VGU, seriya Systemnyi analiz i informatsionnye tekhnologii [Voronezh state university bulletin, Series system analysis and information technologies]. 2019, no. 3, pp. 42–52.

2. Borovkov A. A. Teoriya veroyatnostei [Probability theory]. Moscow, Nauka, 1986, 432 p.

3. Ermakov S. M., Mikhailov G. A. Kurs statisticheskogo modelirovaniya [Statistical modeling course]. Moscow, Nauka, 1976, 320 p.

4. Litvinenko A. N., Grachev A. V., Tarashnina S. I., Britvina I. I. Otsenka veroyatnosti rosta ugroz ekonomicheskoi bezopasnosti na osnove postroeniya klassifikatsionnykh funktsii [Estimation of the probability of growth for the threats of economic security based on classification functions]. Izvestiya Yugo-Zapadnogo gosudarstvennogo universiteta. Seriya ekonomika, sotsiologiya, menedzhment [Bulletin of South-West state university. Series economics, sociology, management]. 2019, vol. 9, no. 2 (31), pp. 129–147.

5. Loginov K. K. Vychislenie vesovykh koeffitsientov v integral'nom indekse ekonomicheskoi bezopasnosti regiona na primere Omskoi oblasti [Calculation of weight coefficients in the integral index of economic security of the region in terms of Omsk region]. Nauka o cheloveke: gumanitarnye issledovaniya [Human science: humanitarian researches]. 2020, no. 1 (39), pp. 186–194.

6. Loginov K. K., Korableva A. A., Karpov V. V. Prognozirovanie indikatorov ekonomicheskoi bezopasnosti Omskoi oblasti v srednesrochnoi perspektive [Forecasting indicators of economic safety of the Omsk region in the medium- term perspective]. Nauka o cheloveke: gumanitarnye issledovaniya [Human science: humanitarian researches]. 2018, no. 4 (34), pp. 174–182.

7. Loginov K. K., Korableva A. A., Karpov V. V. Ekonomicheskaya bezopasnost' regionov Sibirskogo federal'nogo okruga [Economic security of the Siberian federal district regions]. Nauka o cheloveke: gumanitarnye issledovaniya [Human science: humanitarian researches]. 2018, no. 1 (31), pp. 141–150.

8. Mityakov E. S., Sazontov V. A. Ispol'zovanie algoritmov adaptivnoi fil'tratsii dlya prognozirovaniya ekonomicheskoi dinamiki [Application of adaptive filtration algorithms to forecast economic dynamics]. Trudy NGTU im. R. E. Alekseeva [Proceedings of Nizhny Novgorod state technical university n.a. R. E. Alekseev]. 2012, no. 2 (95), pp. 339–344.

9. Mityakov E. S., Mityakov S. N. Otsenka riskov v zadachakh monitoringa ugroz ekonomicheskoi bezopasnosti [Assessment of risks in problems of monitoring of threats of economic security]. Trudy NGTU im. R. E. Alekseeva [Proceedings of Nizhny Novgorod state technical university n.a. R. E. Alekseev]. 2018, no. 1 (120), pp. 44–51.

10. Mityakov S. N., Mityakov E. S., Romanova N. A. Ekonomicheskaya bezopasnost' regionov Privolzhskogo federal'nogo okruga [The economic security of the Volga federal district regions]. Ekonomika regiona [Economy of the region]. 2013, no. 3 (35), pp. 81–91.

11. Mikhailov G. A., Voitishek A. V. Chislennoe statisticheskoe modelirovanie. Metody Monte-Karlo [Numerical statistical modeling. Monte Carlo methods]. Moscow, Akademiya, 2006, 368 p.

12. Naumova O. A., Tyugin M. A. Metodika monitoringa finansovoi bezopasnosti ekonomicheskogo subekta na osnove otsenki riska nastupleniya finansovykh ugroz [The technique of monitoring the financial security of the economic entity based on the assessment of financial threatening risk]. Vektor nauki TGU. Seriya ekonomika i upravlenie [Vector of science of Togliatti State University. Series economics and management]. 2018, no. 2 (33), pp. 34–41.

13. Sevastianov B. A. Vetvyashchiesya protsessy [Branching processes]. Moscow, Nauka, 1971, 436 p.

14. Tikhonov V. I., Mironov M. A. Markovskie protsessy [Markov processes]. Moscow, Sovetskoe radio, 1977, 488 p.

15. Frenkel A. A., Volkova N. N., Romanyuk E. I. Vliyanie vesovykh koeffitsientov na reiting regionov po urovnyu innovatsionnogo potentsiala [Weighing coefficients and innovation potential ratings in regions]. Region: ekonomika i sotsiologiya [Region: economics and sociology]. 2013, no. 1 (77), pp. 144–172.

16. Marchenko M. A., Mikhailov G. A. Parallel realization of statistical simulation and random number generators. Russ. J. Numer. Anal. Math. Mod. 2002, vol. 17, pp. 113–124.

17. Marchenko M. PARMONC – A Software Library for Massively Parallel Stochastic Simulation. In: Parallel Computing Technologies, PaCT 2011. Lecture Notes in Computer Science, Ed. Malyshkin V. Springer, Berlin, Heidelberg. 2011, vol. 6873, pp. 302–316.


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Loginov K.K., Karpov V.V., Korableva A.A. ESTIMATION OF FINAL DISTRIBUTION OF PROBABILITIES OF THREATS REALIZATION IN THE SPHERE OF ECONOMIC SECURITY BASED ON SIMULATION MODELING. Herald of Siberian Institute of Business and Information Technologies. 2021;10(1):67-75. (In Russ.) https://doi.org/10.24412/2225-8264-2021-1-67-75

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