System approach to forecasting and preparedness of response to emergency situations

User Rating:  / 0
PoorBest 

Authors:


H.V.Ivanets, orcid.org/0000-0002-4906-5265, National University of Civil Defence of Ukraine, Kharkiv, Ukraine, -mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

S.A.Horielyshev, orcid.org/0000-0003-1689-0901, National Academy of the National Guard of Ukraine, Kharkiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

D.S.Baulin, orcid.org/0000-0002-7082-6954, National Academy of the National Guard of Ukraine, Kharkiv, Ukraine, e-mail: baulinds1966@ukr.net

M.H.Ivanets, orcid.org/0000-0002-3106-7633, Ivan Kozhedub Kharkiv National University of Air Force, Kharkiv, Ukraine, -mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

O.O.Novykova, orcid.org/0000-0003-3557-5210, National Academy of the National Guard of Ukraine, Kharkiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.


повний текст / full article



Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2020, (6): 109 - 114

https://doi.org/10.33271/nvngu/2020-6/109



Abstract:



Purpose.
Development of system approach and formation of complex methods for joint forecasting of emergency situations (ES) and ensuring the preparedness of the response of civil protection units in real conditions.


Methodology.
When developing methods for predicting ES and possible damage as result of them, polynomial-regression method with varied order, weighted least square method, probabilistic-statistical method, methods of time series and mathematical statistics were used. When developing models of resource provision of preparedness for emergency response, methods of regression analysis, time series and mathematical statistics were used. The principle of forecasting the costs of funds for the elimination of the consequences of ES is based on the fact that they are determined by the costs of eliminating man-made and natural emergencies. When choosing models for predicting technical support and the number of personnel required for emergency response, we proceeded from the fact that they should be determined not only by the predicted number of ES, but also by their nature. The model for optimization of territorial structures of civil protection (CP) is based on the principle of compliance of the number of regional structures with the level of threats in these territories. Methods of mathematical statistics and mathematical modeling were used in the study on the effectiveness of the application of system approach to joint forecasting and provision of preparedness for emergency response.


Findings.
Methods for forecasting the processes of emergencies and damage as a result of them, models for optimizing territorial structures of civil protection, taking into account the state of man-made natural hazards in the regions of the state, forecasting technical support and the number of personnel to eliminate possible emergencies.


Originality.
Asystem approach to solving the problem of joint forecasting of ES and maintaining the preparedness of response of civil protection units in order to minimize the consequences of these situations is proposed.


Practical value.
The proposed set of methods and models is the foundation for substantiating organizational and technical measures to prevent and adequately respond to emergencies both on national scale and in the countrys regions.


Keywords:
emergency, civil protection, preparedness of response, resource support, model

References.


1. 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. https://doi.org/10.2298/ijgi1303227g.

2. Dubinin, D., Korytchenko, ., Lisnyak, ., 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.

3. Rybalova, O., Artemiev, S., Sarapina, M., Tsymbal, B., Bakharev, 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.

4. Bakharev, A., Shestopalov, O., Filenko, O., Tykhomyrova,T., Rybalova, O., Artemiev, S., & 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.

5. Tiutiunyk, V.V., Ivanets, H.V., Tolkunov, I.A., & Stetsyuk,E.I. (2018). System approach for readiness assessment units of civil defense to actions at emergency situations. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, (1), 99-105. https://doi.org/10.29202/nvngu/2018-1/7.

6. Ivanets, G.V., & Gorelyshev, S.A. (2016). Assessment of the level of technogenic-natural-social danger of regions of the state based on the method of vector-statistical analysis, taking into account the area of their territory and the number of population. Scientific journal POWER AND SOCIETY, 3(39), 162-174.

7. Novoselov, S.V., & Panikhidnikov, S.A. (2017). Problems of predicting the number of emergencies by statistical methods. Mining information and analytical bulletin, (10), 60-71.

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

9. Pospelov, B., Andronov, V., Rybka, E., Meleshchenko, R., & Gornostal, S. (2018). Analysis of correlation dimensionality of the state of a gas medium at early ignition of materials. Eastern-European Journal of Enterprise Technologies, 5(10(95)), 25-30. https://doi.org/10.15587/1729-4061.2018.142995.

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

11. 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. https://doi.org/10.15587/1729-4061.2018.121727.

12. Kryanev, A., Ivanov, V., Romanova, A., Sevastianov, L., & Udumyan, D. (2018). Extrapolation of Functions of Many Variables by Means of Metric Analysis. EPJ Web of Conferences, 173:03014. https://doi.org/10.1051/epjconf/201817303014.

13. Sun, B.Z., Ma, W.M., & Zhao, H.Y. (2013). A Fuzzy Rough Set Approach to Emergency Material Demand Prediction over Two Universes. Applied Mathematical Modelling, 37, 7062-7070. https://doi.org/10.1016/j.apm.2013.02.008.

14. 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.

15. Zhuang, Yue (2017). Constructing Effective Mechanism of Reflection on Major Accidents Zhang Supei. China Safety Science Journal, (6), 1-6.

16. Martha, A., & Centeno, A. (2014). Markov chain location-allocation meta-model for hurricane relief planning. International Journal of Emergency Management, 10(3/4), 209-240. https://doi.org/10.1504/IJEM.2014.066477.

17. West Virginia State Fire Commission. Requirements for West Virginia Fire Departments (n.d.). Retrieved from http://www.firemarshal.wv.gov/Documents/Multimedia.

18. Ivanets, G.V., Pospelov, B.B., Tolkunov, I.A., Stetsyuk,E.I., & Ivanets, M.G. (2017). Model for forecasting emergencies: the regional dimension. East journal of security studies. Collection of scienstific papers, 2/2, 41-55.

19. Analytical review of the state of man-made and natural security in Ukraine in 2017. UkrRI CSUE (2018). Kyiv. Retrieved from https://www.dsns.gov.ua/files/prognoz/report/2017/%D0%90%D0%9E_2017.pdf.

20. Report on the main results of the Civil Service of Ukraine for Emergencies in 2018 (n.d.). Retrieved from http://www.dsns.gov.ua/files/2018/1/26/Zvit%202017(). pdf.

 

Visitors

3252861
Today
This Month
All days
333
5495
3252861

Guest Book

If you have questions, comments or suggestions, you can write them in our "Guest Book"

Registration data

ISSN (print) 2071-2227,
ISSN (online) 2223-2362.
Journal was registered by Ministry of Justice of Ukraine.
Registration number КВ No.17742-6592PR dated April 27, 2011.

Contacts

D.Yavornytskyi ave.,19, pavilion 3, room 24-а, Dnipro, 49005
Tel.: +38 (056) 746 32 79.
e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
You are here: Home About the journal concept of the journal EngCat Archive 2020 Content №6 2020 System approach to forecasting and preparedness of response to emergency situations