FORMALIZED MATHEMATICAL MODEL OF COMPATIBLE FORECASTING AND ENSURING READINESS FOR EMERGENCY SITUATION RESPONSE

Authors

  • H. Ivanets
  • M. Ivanets
  • I. Tolkunov
  • I. Popov

DOI:

https://doi.org/10.26906/SUNZ.2021.2.112

Keywords:

formalized mathematical model, control algorithm, emergency situation, losses from emergencies, level of readiness

Abstract

Topicality. At present, emergency prevention should be seen as a complex, combined process of predicting emergencies and responding in advance to threats or mitigation. Goal. Development of a formalized mathematical model of joint emergency forecasting and ensuring emergency preparedness. Method. The formalized mathematical model of joint forecasting and ensuring the readiness to respond to emergencies is a system of analytical dependencies, which together allow to solve the problem of research. It implements the principle of a systematic approach to solving the problem of emergency prevention in order to prevent their occurrence or minimize the possible consequences. Emergency prevention is a complex systemic process related to the analysis of emergency threats, their forecasting and ensuring the readiness of civil defense units to respond. Results. A formalized mathematical model of joint forecasting and ensuring emergency response preparedness and a control algorithm that implements the developed mathematical model have been developed. The formalized mathematical model of joint forecasting and emergency preparedness is a combination of twointerrelated models: the emergency forecasting model and the possible damage caused by them, and the emergency preparedness model. Conclusions. Formalized mathematical model of joint forecasting and emergency preparedness includes mathematical models of emergency forecasting by nature, types, levels and possible consequences as a result of them both in the state as a whole and in its regions; mathematical models for assessing the potential technical capacity and readiness of units to perform tasks as assigned, optimal allocation of resources to ensure the readiness of units, optimization of territorial structures of civil defense, cost forecasting, technical and human support for emergencies. The obtained results of the research are the foundation for substantiation of organizational and technical measures for adequate response to emergencies of different nature in real conditions.

Downloads

References

Rybalova, O., Artemiev, S., Sarapina, M., Tsymbal, B., Bakharevа, A., Shestopalov, O., Filenko, O. (2018). Development of methods for estimating the environmental risk of degradation of the surface water state. Eastern-European Journal of Enterprise Technologies. 2(10 (92)), 4–17. https://doi.org/10.15587/1729-4061.2018.127829.

Bakharevа, A., Shestopalov, O., Filenko, O., Tykhomyrova, T., Bryhada, O. (2018). Studying the influence of design and operation mode parameters on efficiency of the systems of biochemical purification of emissions. Eastern-European Journal of Enterprise Technologies, 3(10(93)), 59–71. https://doi.org/10.15587/1729-4061.2018.133316.

Guskova, N.D., Neretina, E.A. (2013). Threats of natural character, factors affecting sustainable development of territories and their prevention. Journal of the Geographical Institute Jovan Cvijic, SASA, 63(3), 227–237.

Dubinin, D., Korytchenko, K., Lisnyak, A., Hrytsyna, I., Trigub, V. (2017). Numerical simulation of the creation of a fire fighting barrier using an explosion of a combustible charge. Eastern-European Journal of Enterprise Technologies, 6(10 (90), 11–16. https:// doi.org/ 10.15587/1729-4061.2017.114504.1. 5. Nivolianitou Z., Synodinou B. A Towards emergency management of natural disasters and critical accidents: The Greek experience // Journal of Environmental Management. 2011. Vol. 92, Issue. 10, 2657–2665.

Новоселов С.В., Панихидников С.А. Проблемы прогнозирования количества чрезвычайных ситуаций статистическими методами // Горный информационно-аналитический бюллетень. 2017. No10, 60–71.

Deng, S.C., Wu, Q., Shi, B. (2014) Prediction of Resource for Responding Waterway Transportation Emergency Based on Case-Based Reasoning // China Safety Science Journal, 24, 79–84.

Vasiliev M., Movchan I., Koval O. Diminishing of ecological risk via optimization of fire-extinguishing system projects in timber-yards // Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2014. Issue 5, 106–113.

Mygalenko, K., Nuyanzin, V., Zemlianskyi, A., Dominik, A., Pozdieiev, S. (2018). Development of the technique for restricting the propagation of fire in natural peat ecosystems // Eastern-European Journal of Enterprise Technologies, 1 (10(91)), 31–37.

Sun, B.Z., Ma, W.M. and Zhao, H.Y. (2013) A Fuzzy Rough Set Approach to Emergency Material Demand Predictiono ver Two Universes. Applied Mathematical Modeling, 37, 7062–7070. http://dx.doi.org/10.1016/j.apm.2013.02.008.

Development of combined method for predicting the process of the occurrence of emergencies of natural character. / Ivanets H., Horielyshev S., Ivanets M., D. Baulin, Tolkunov I., Gleizer N., Nakonechnyi A. //Eastern-European Journal of Enterprise Technologies. 2018. Vol. 5, Issue 10(95), 48–55. doi:https://doi.org/10.15587/1729-4061.2018.143045.

Неклонський І.М., Самарін В.О., Харламов В.В. Спектральний підхід до оцінювання готовності аварійно-рятувальних підрозділів до дій за призначенням / Проблеми надзвичайних ситуацій. Х.: НУЦЗУ, 2016. Вип. 23, 113–120.

Самарин В.А., Сокол Я.С. Модель готовности спасательных систем, использующих техническое оснащение для проведения аварийно-спасательных работ. Проблеми надзвичайних ситуацій. Х.: НУЦЗУ, 2015. Вип. 21, 76–82.

Самарін В.О. Модель готовності складових рятувальних сил до дій за призначенням / В.О. Самарін, І.М. Неклонський, Д.Л. Соколов // Проблеми надзвичайних ситуацій: зб. наук. пр. Харків: НУЦЗУ, 2015. Вип. 22, 113–118.

Власов К.С., Денисов А.Н. Методика анализа показателей оперативного реагирования пожарно-спасательных подразделений // Технология техногенной безопасности, 2016. No 3(67), 207–213.

Lee, Yohan, Byungdoo Lee, and Kyung Ha Kim (2014). Optimal spatialallocation of initial attack resources for firefighting in the republic of Korea using a scenario optimization model. Journal of Mountain Science, 11.2, 323–335.

Martha A. Centeno A Markov chain location-allocation meta-model for hurricane relief planning / Martha A. Centeno, Desiree Tejada-Calvo// Int. J. of Emergency Management. 2014 Vol.10. No.3/4, 209–240.

Рогозін А.С. Оптимізація розподілу сил цивільного захисту по регіонах України / А.С. Рогозін, О.В. Пирогов, Є.А. Яровий // Проблеми надзвичайних ситуацій. Харків: НУЦЗУ, 2016. Вип. 23, 134–140.

Іванець Г.В., Іванець М.Г., Матухно В.В., Толкунов І.О., Стецюк Є.І., Попов І.І. Формалізована математична модель прогнозування надзвичайних ситуацій та можливих завданих збитків внаслідок них // Системи управління, навігації та зв’язку. Полтава: ПНТУ, 2020. Вип. 4(62), 92–97.

Published

2021-05-31