Дата поступления: 
20.11.2019
Год: 
2019
Номер журнала (Том): 
УДК: 
519.862.6
Файл статьи: 
Страницы: 
17
22
Аннотация: 

The paper discusses the problem of modeling forest fires in the Irkutsk region according to annual data from 2019. Forest fires cause great damage to the natural and material resources of the Russian Federation; therefore, this problem should be given primary attention, including their mathematical modeling. One of the main reasons for the difficult situation with forest fire research is the lack of a comprehensive scientific basis (basic methodology) for both qualitative and quantitative analysis of the forecast of the occurrence, spread and suppression of forest fires. In this paper, regression analysis is considered as the main tool for mathematical modeling and data analysis. A regression model is obtained in the form of a trigonometric dependence.

Список цитируемой литературы: 

1. Daneev A.V., Udilov T.V., Rusanov V.A. To methods of operational forecasting of the front of a forest fire. I. // Modern technologies. System analysis. Modeling. Number 3, 2008. - pp. 38-46.

2. Daneev A.V., Udilov T.V., Rusanov V.A. To methods of operational forecasting of the front of a forest fire. Ii. // Modern technologies. System analysis. Modeling. № 4, 2008. - p. 27-35.

3. Bazilevskij M.P., Noskov S.I. Modelirovanie obstanovki s pozharami v sel'skih naselennyh punktah v usloviyah ih gazifikacii [Modeling of the situation with fires in rural areas in the conditions of their gasification]. Informacionnye tekhnologii i problemy matematicheskogo modelirovaniya slozhnyh system [Information technologies and problems of mathematical modeling of complex systems]. Irkutsk, IrGUPS, 2012, no. 10, pp. 65-71.

4. Ajvazyan S.A., Enyukov I.S., Meshalkin L.D. Prikladnaya statistika: Issledovanie zavisimostej [Applied Statistics: Addiction Research]. Moscow, Finance and Statistics, 1985, 487 p.

5. Draper N.R., Smith H. Applied regression Analysis, 3rd edition. John Wiley & Sons, 1998, 736 p.

6. Dougerti K. Vvedenie v ehkonometriku [Introduction in Econometrics]. Moscow, Infra-M, 2009, 465 p.

7. Noskov S.I., Bazilevskij M.P. Postroenie regressionnyh modelej s ispol'zovaniem apparat linejno-bulevogo programmirovaniya [Construction of regression models using linear-boolean programming device]. Irkutsk, IrGUPS, 2018, 176 p.

8. Bazilevskij M.P. Razrabotka i issledovanie algoritmov ocenivaniya parametrov additivnoj stepennoj regressii [Development and research of algorithms for estimating additive power regression parameters] // Sovremennye tekhnologii. Sistemnyj analiz. Modelirovanie [Modern technologies. System analysis. Modeling], 2017 , no. 4, vol. 56, pp. 131-138.