The practice of connectionist model for predicting forest fires in the Arctic zones of the Krasnoyarsk Territory : научное издание

Описание

Тип публикации: статья из журнала

Год издания: 2020

Идентификатор DOI: 10.1007/s13198-019-00786-w

Ключевые слова: forest fires, monitoring of emergencies, north of krasnoyarsk region, forecasting emergencies, connectionist network

Аннотация: This paper presents data on the localization and number of forest fires that occur in the Arctic zones of the Krasnoyarsk Territory, as well as the possible causes of their occurrence. It is established that the main cause of forest and landscape fires are natural phenomena. A database of data normalized in a certain way about the Показать полностьюfactors shaping the occurrence of natural forest and landscape fires has been formed. The practice of connectionist algorithms, a forecasting model has been developed, and, based on data on forest and landscape fires in the Krasnoyarsk Territory; a model has been evaluated for using the model to predict fires in 2018. In order to compile a forecast of forest and landscape fires for 2019 in the Arctic zones of the Krasnoyarsk Territory using the connectionist algorithms, an optimal neuroarchitecture was chosen, which allows long-term time series forecasting.

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Издание

Журнал: INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT

Выпуск журнала: Vol. 11, Is. SUPPL 1

Номера страниц: 1-9

ISSN журнала: 09756809

Место издания: NEW DELHI

Издатель: SPRINGER INDIA

Персоны

  • Grebnev Yaroslav (Siberian Fed Univ, 79 Svobodny Pr, Krasnoyarsk 660041, Russia; Head Off Emercom Russia Krasnoyarsk Terr, Ctr Crisis Management, Krasnoyarsk, Russia)
  • Moskalev Alexander (Siberian Fed Univ, 79 Svobodny Pr, Krasnoyarsk 660041, Russia)
  • Vershkov Anatoliy (Siberian Fed Univ, 79 Svobodny Pr, Krasnoyarsk 660041, Russia)
  • Gazizulina Albina (Peter Great St Petersburg Polytech Univ, Polytech Skaya 29, St Petersburg 195251, Russia)