Deterministic-Probabilistic Approach to Predict Lightning-Caused Forest Fires in Mounting Areas; Forecasting; Vol. 3, iss. 4

Podrobná bibliografie
Parent link:Forecasting
Vol. 3, iss. 4.— 2021.— [P. 695-715]
Hlavní autor: Baranovskiy N. V. Nikolay Viktorovich
Korporativní autor: Национальный исследовательский Томский политехнический университет Инженерная школа энергетики Научно-образовательный центр И. Н. Бутакова (НОЦ И. Н. Бутакова)
Shrnutí:Title screen
Forest fires from lightnings create a tense situation in various regions of states with forested areas. It is noted that in mountainous areas this is especially important in view of the geophysical processes of lightning activity. The aim of the study is to develop a deterministic-probabilistic approach to predicting forest fire danger due to lightning activity in mountainous regions. To develop a mathematical model, the main provisions of the theory of probability and mathematical statistics, as well as the general theory of heat transfer, were used. The scientific novelty of the research is due to the complex use of probabilistic criteria and deterministic mathematical models of tree ignition by a cloud-to-ground lightning discharge. The paper presents probabilistic criteria for predicting forest fire danger, taking into account the lightning activity, meteorological data, and forest growth conditions, as well as deterministic mathematical models of ignition of deciduous and coniferous trees by electric current of a cloud-to-ground lightning discharge. The work uses synthetic data on the discharge parameters and characteristics of the forest-covered area, which correspond to the forest fire situation in the Republic of Altay and the Republic of Buryatia (Russian Federation). The dependences of the probability for occurrence of forest fires on various parameters have been obtained.
Jazyk:angličtina
Vydáno: 2021
Témata:
On-line přístup:https://doi.org/10.3390/forecast3040043
Médium: Elektronický zdroj Kapitola
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=666628

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330 |a Forest fires from lightnings create a tense situation in various regions of states with forested areas. It is noted that in mountainous areas this is especially important in view of the geophysical processes of lightning activity. The aim of the study is to develop a deterministic-probabilistic approach to predicting forest fire danger due to lightning activity in mountainous regions. To develop a mathematical model, the main provisions of the theory of probability and mathematical statistics, as well as the general theory of heat transfer, were used. The scientific novelty of the research is due to the complex use of probabilistic criteria and deterministic mathematical models of tree ignition by a cloud-to-ground lightning discharge. The paper presents probabilistic criteria for predicting forest fire danger, taking into account the lightning activity, meteorological data, and forest growth conditions, as well as deterministic mathematical models of ignition of deciduous and coniferous trees by electric current of a cloud-to-ground lightning discharge. The work uses synthetic data on the discharge parameters and characteristics of the forest-covered area, which correspond to the forest fire situation in the Republic of Altay and the Republic of Buryatia (Russian Federation). The dependences of the probability for occurrence of forest fires on various parameters have been obtained. 
461 |t Forecasting 
463 |t Vol. 3, iss. 4  |v [P. 695-715]  |d 2021 
610 1 |a труды учёных ТПУ 
610 1 |a электронный ресурс 
610 1 |a forest fire 
610 1 |a danger 
610 1 |a probability 
610 1 |a lightning 
610 1 |a deterministic 
610 1 |a probabilistic 
610 1 |a prediction 
610 1 |a mounting area 
610 1 |a лесные пожары 
610 1 |a опасность 
610 1 |a молния 
700 1 |a Baranovskiy  |b N. V.  |c specialist in electrical engineering  |c Associate Professor of Tomsk Polytechnic University, Candidate of physical and mathematical sciences  |f 1978-  |g Nikolay Viktorovich  |3 (RuTPU)RU\TPU\pers\34172  |9 17706 
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