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

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Abstract

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 factors 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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Acknowledgements

The research carried out with the financial support of the grant from the Program Competitiveness Enhancement of Peter the Great St. Petersburg Polytechnic University. The article is prepared in the frameworks of the research net “Innovation development of Russian Arctic regions and economic sectors”, “National Arctic Scientific-Educational Consortium” association. We are thankful to the team of the Center of Academic Writing of Tyumen State University, Zhuravleva Nadezhda and Valeria Evdash who lent a professional support in preparing this manuscript.

Funding

The research carried out with the financial support of the grant from the Program Competitiveness Enhancement of Peter the Great St.Petersburg Polytechnic University, Project 5-100-2020.

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Correspondence to Albina Gazizulina.

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Grebnev, Y., Moskalev, A., Vershkov, A. et al. The practice of connectionist model for predicting forest fires in the Arctic zones of the Krasnoyarsk Territory. Int J Syst Assur Eng Manag 11 (Suppl 1), 1–9 (2020). https://doi.org/10.1007/s13198-019-00786-w

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