У статті пропонується методологія моделювання комплексних систем інженерії, яка буде корисною для дослідників та операторів складних технічних систем при прогнозуванні надзвичайних ситуацій за допомогою систем моніторингу навколишнього середовища.
The paper considers the issues of predicting the situations and optimizing decision-making to improve the environmental situations in the areas with industrial pollution based on the finite Markov’s chains. The article systematizes the existing approaches to forecasting technological risks. The problems associated with the search for optimal forms of environmental safety management and approaches for predicting anthropogenic impact on the environment using mathematical models are considered. To predict the state of the environment, stochastic modeling is proposed, the basis of which is the theory of finite Markov chains. A technique for predicting and optimizing the economic effect on a discrete set of strategies has been developed. The figures show: building system states graph, determining the basic characteristics of system states, finding transition probabilities of Markov chains for non-critical states, a typical cycle of checking the model’s adequacy and system quality. Based on the analysis of existing approaches to forecasting technological risks, a methodology has been developed for forecasting and optimizing the economic effect on a discrete set of strategies. The proposed methodology allows combining economic estimates with the ability to predict the situations and optimize decision-making to improve the environmental situation in the areas of possible chemical pollution. Using the developed methodology will increase the efficiency of the industrial enterprises, facilitate generating informed management decisions, create software and hardware ways to respond the emergencies. The methodology for modeling engineering within nature complex systems and the optimization of decision-making based on finite Markov chains in the areas with industrial pollution will be helpful to researchers and operators of complex technical systems in predicting emergencies using environmental monitoring systems.
- Himmelblau D. Detection and diagnosis of malfunctions in chemical and petrochemical processes/D.Himmelblau; per. from English–L-.:Сhemistry,1983.-352p.
- The methodology for predicting the availability of viliva (Wikidu) of non-secure chemical speeches in case of accidents at industrial sites and transport [Electronic resource]. - Access mode: http://zakon4.rada.gov.ua/laws/show/z0326-01
- Pankratova N.D. Recognition of an emergency in the dynamics of the operation of a technologically dangerous object /N.D.Pankratova, A.M.Raduk//Scientific news NTUU «KPU». -2008.-No.3.-P.43–52.
- Getun G.V. Differential processes with cumulative characteristics during operation / Getun G.V., Butsenko Yu.P., Balina O.I., Bezklubenko I.S., Solomin A.V. // Optical materials and theory equipment. - 2019.No102. - Р.243-252.
- Malinetskii G.G. Modern problems of nonlinear dynamics / G. G. Malinetskii, A. B. Potapov. - M.: Editorial URSS, 2000.-336 p.
- Demidenko E.Z. Optimization and regression / E.Z. Demidenko. -M.:Nauka,1989.-296p.
- Li Ts. Estimation of parameters of Markov models by aggregated time series / Ts. Li, D. Judge, A. Zelner; per. from English - M.: Statistics, 1977.- 221 p.
- Bardin I.V. Prediction of situations and optimization of decision-making on improving the environmental situation in areas with oil pollution based on finite Markov chains / I.V. Bardin, Yu. D. Motorygin, M.A. Galishev // Problems of risk management in the technosphere . - 2009. - No. 1–2. - p. 17–23.
- Admaev O.V. Use of Markov processes for assessing the environmental safety of an airspace of a city / O.V. Admaev, T.V. Gavrilenko // Optics of the atmosphere and ocean. - 2010. - T. 23, No. 12. - p. 1087-1090.
- Karmanov A.V. Research of controlled finite Markov chains with incomplete information (minimax approach) / V.A. Karmanov. - M.: Fizmatlit, 2002. ‑ 176 p.
- Khabarov V. I. Markov model of transport correspondence / V.I. Khabarov, D.O. Molodtsov, S.G. Khomyakov // Reports of TUSUR. - 2012. - No. 1 (25), part 1. - p. 113–117.
- Priymak, M.V. Periodic Markov Lanterns in the tasks of statistical analysis and forecasting energy supply / M.V. Priymak // Technical electrodynamics. - 2004. - No. 2. - Р. 3–7.