Национальный цифровой ресурс Руконт - межотраслевая электронная библиотека (ЭБС) на базе технологии Контекстум (всего произведений: 645537)
Контекстум
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Первый авторShchetinin
Страниц4
ID404336
АннотацияThe wildfire (forest fire) is a natural disaster that causes great economical losses in many regions of Russia. In the present work the joint sample of daily values of the number of forest fire seats and the Nesterov meteorological index in Irkutsk region, seasons 1969–1988, are investigated. It appears that the evolution of forest fire is well described by a vector autoregression process based model. The prediction of the future numbers of fire seats can be performed using special computer algorithm, which is shown to produce accurate and reliable estimates up to 2 days ahead.
УДК517.6
Shchetinin, Eu.Yu. Forest Wildfire Modelling and Prediction in Russia / Eu.Yu. Shchetinin // Вестник Российского университета дружбы народов. Серия: Математика, информатика, физика .— 2013 .— №2 .— С. 87-90 .— URL: https://rucont.ru/efd/404336 (дата обращения: 14.07.2024)

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UDC 517.6 Forest Wildfire Modelling and Prediction in Russia Eu. <...> Shchetinin Chair of Applied Mathematics Moscow State Technology University “STANKIN” 3a, Vadkovsky lane, Moscow, Russia, 119136 The wildfire (forest fire) is a natural disaster that causes great economical losses in many regions of Russia. <...> In the present work the joint sample of daily values of the number of forest fire seats and the Nesterov meteorological index in Irkutsk region, seasons 1969–1988, are investigated. <...> The prediction of the future numbers of fire seats can be performed using special computer algorithm, which is shown to produce accurate and reliable estimates up to 2 days ahead. <...> Key words and phrases: forest fires, heteroscedasticity, vector multiplicative seasonal autoregressive coefficient Spearman, forecast. 1. <...> A reliable and accurate forecast allows to wisely allocate limited resources and concentrate on the optimal measures. <...> Common requirements to forest fire monitoring and forecasting are regulated by The phenomenon of forest fire is one of the most devastating natural disasters NI = ∑ i=1 n Russian state standard GOST R 22.1.09–99 “Safety in emergencies. <...> According to this document, the severity of forest fire danger is defined by the complex meteorological index of V. G. Nesterov: T(T −Td), where T is the air temperature (in Celsius degree), Td is the dew point (in Celsius degree), n is the number of days since last precipitation (precipitation values < 2.5mm are ignored) [2]. 2. <...> MAR(1)S Model to the meteorological factors, the joint sample of daily values of the number of forest fire seats and the Nesterov index in Irkutsk region, seasons 1969–1988, has been investigated: To assess statistical properties of the forest fire evolution process and its relation Xtk = (FStk NItk ) , k = p · kp, where p = 20 is the number of seasons (periods), kp = 214 is the number of observations per season (from April 1 to October 31, fig. 1). <...> Raw data – bivariate skew-normal [4] random component etk xtk = exp(ytk +s(τtk)), , . ytk = A· yt−1 <...>