Математико-статистическая модель прогнозирования количества пожаров для использования в системе МЧС России
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Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

Mathematical and statistical fire incidence forecasting model for use in the EMERCOM system of Russia

Kistanova L.A.   idRepin S.V. Boldyrevsky P.B.   Lakhvitsky G.N.  

UDC 614.8:519.2
DOI: 10.26102/2310-6018/2022.37.2.002

  • Abstract
  • List of references
  • About authors

Making and analysing fire incidence forecasts is the issue which is in the focus of the attention of the supervisory activity directorate of the Ministry of the Russian Federation for Civil Defence, Emergencies and Elimination of Consequences of Natural Disasters because it concerns safety of human life and, thus, the tasks of solving this problem, and therefore planning and optimization of unit personnel. At the same time, about 30% of the control measures total number, carried out by fire supervision authorities, pertained to scheduled inspections. This article demonstrates the correlation between fire dynamics forecasting and scheduled inspections and determines the magnitude of the lag or delay in conducting scheduled inspections in relation to the number of fires. The mathematical and statistical model is based on the example of statistical data on the fire incidence in the Nizhny Novgorod region and the Russian Federation from 2010 to 2020. To define and address this problem, the mathematical apparatus of time series theory was used, in particular, the method with distributed lags - the Almon technique. The findings allow us to conclude that mathematical models with distributed lags, performed by means of the Almon technique, can be employed to predict fire incidence in the EMERCOM of Russia system, as well as to schedule inspections of the state fire services of the EMERCOM of Russia and formulate proposals for optimizing the personnel of the EMERCOM units.

1. Baturo A.N. Forecasting the number of fires in the region based on the theory of time series. Civil security technologies. 2013;10(3):84–88. (In Russ.)

2. Kudryavtsev V.E., Kuchakov R.K. Do routine inspections help reduce the number of fires? Pozharovzryvobezopasnost = Fire and Explosion Safety. 2019;28(2):81–89. Available at: https://doi.org/10.18322/PVB.2019.28.02.81-89 (accessed: 27.10.2021). (In Russ.)

3. Pranov B.M. On some approaches to modeling and forecasting time series of fire statistics. Tekhnologii tekhnosfernoj bezopasnosti = Technology of technosphere safety. 2014;5(57). Available at: http://agps-2006.narod.ru/ttb/2014-5/23-05-14.ttb.pdf (accessed: 14.09.2021). (In Russ.)

4. Materov E.N. The use of the R programming language in matters of fire safety: analysis of the statistics of the number of fires based on the theory of time series. Scientific and analytical journal "Sibirskiy pozharno-spasatel'nyy vestnik = Siberian Fire and Rescue Bulletin". 2019;1(12):52–57. Available at: http://vestnik.sibpsa.ru/wp-content/uploads/2019/v1/N12_52-57.pdf (accessed 19.10.2021). (In Russ.)

5. Gorbenko O.N., Makarova A.A. Analysis of modern methods used in modeling fires. Modelirovaniye, optimizatsiya i informatsionnyye tekhnologii = Modeling, optimization and information technology. 2013;1(2). Available at: https://moit.vivt.ru/wp-content/uploads/2013/08/gorbenkomakarova_2_13_2.pdf (accessed: 20.10.2021). (In Russ.)

6. Boldyrevskiy P.B., Kistanova L.A. Model with distributed lags of the dynamics of innovation activity of industrial enterprises. Ekonomicheskiy analiz: teoriya i praktika = Economic analysis: theory and practice. 2014;25(376):58–62. (In Russ.)

7. Pozhary i pozharnaya bezopasnost’ v 2014 godu: Statisticheskij sbornik. Pod. obsh. red. A.V. Matyushin. Moscow: VNIIPO. 2015:124. (In Russ.)

8. Pozhary i pozharnaya bezopasnost’ v 2016 godu: Statisticheskij sbornik. Pod. obsh. red. D.M. Gordienko. Moscow: VNIIPO. 2017:124. (In Russ.)

9. Pozhary i pozharnaya bezopasnost’ v 2018 godu: Statisticheskij sbornik. Pod. obsh. red. D.M. Gordienko. Moscow: VNIIPO. 2019:125. (In Russ.)

10. Pozhary i pozharnaya bezopasnost’ v 2020 godu: Statisticheskij sbornik. Pod. obsh. red. D.M. Gordienko. Moscow: VNIIPO. 2021:112. (In Russ.)

11. Bogdanova E.M. Prognozirovanie pozharov na osnove avtoregressionnyh modelej. Application of mathematical methods to solving problems of the Ministry of Emergency Situations of Russia: proceedings of section N 15 of the XXVIII International Scientific and Practical Conference "Predotvrashchenie. Spasenie. Pomoshch." FGBVOU VO the AGZ of the Ministry of Emergency Situations of Russia. 2018;52–58. Available at: https://amchs.ru/upload/iblock/9b8/Sbornik-sektsii-15_-KAF.37-KAF.72_.pdf (date of application 23.08.2021). (In Russ.)

12. Konopelko L.A., Rastoskuev V.V., Kustikova M.A., Banar S.A., Bykovskaya E.A., Mayurova A.S. Matematicheskoe modelirovanie v tekhnosfernoj bezopasnosti. St. Petersburg: ITMO University. 2018:65. (In Russ.)

Kistanova Lyudmila Anatolyevna

Email: lakistanova@mail.ru

Nizhny Novgorod State Agricultural Academy

Nizhny Novgorod, Russian Federation

Repin Sergey Viktorovich

Email: repin52@yandex.ru

ORCID |

the Main Directorate of the Ministry of Emergency Situations of Russia in the Nizhny Novgorod Region

Nizhny Novgorod, Russian Federation

Boldyrevsky Pavel Borisovich
Doctor of Physical and Mathematical Sciences Professor

National Research Nizhny Novgorod State University n.a. N.I. Lobachevsky

Nizhny Novgorod, Russian Federation

Lakhvitsky Georgy Nikolaevich

Email: egor70288@mail.ru


the Main Directorate of the Ministry of Emergency Situations of Russia in the Nizhny Novgorod Region

Nizhny Novgorod, Russian Federation

Keywords: EMERCOM of Russia, fire incidence, scheduled inspections, mathematical and statistical forecasting model, time series, model with distributed lags, the Almon technique

For citation: Kistanova L.A. Repin S.V. Boldyrevsky P.B. Lakhvitsky G.N. Mathematical and statistical fire incidence forecasting model for use in the EMERCOM system of Russia. Modeling, Optimization and Information Technology. 2022;10(2). Available from: https://moitvivt.ru/ru/journal/pdf?id=1091 DOI: 10.26102/2310-6018/2022.37.2.002 .

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Full text in PDF

Received 22.11.2021

Revised 17.03.2022

Accepted 11.04.2022

Published 12.04.2022