Izvestiya of Saratov University.

Mathematics. Mechanics. Informatics

ISSN 1816-9791 (Print)
ISSN 2541-9005 (Online)


For citation:

Sorokin A. A., Maltseva N. S., Kutuzov D. V., Osovsky A. V. Information processing for the decision support system for fire monitoring of forest areas. Izvestiya of Saratov University. Mathematics. Mechanics. Informatics, 2023, vol. 23, iss. 1, pp. 126-138. DOI: 10.18500/1816-9791-2023-23-1-126-138, EDN: PCOXKQ

This is an open access article distributed under the terms of Creative Commons Attribution 4.0 International License (CC-BY 4.0).
Published online: 
01.03.2023
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Russian
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Article
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005
EDN: 
PCOXKQ

Information processing for the decision support system for fire monitoring of forest areas

Autors: 
Sorokin Alexander A., Astrakhan State Technical University
Maltseva Nataliya S., Astrakhan State Technical University
Kutuzov Denis V., Astrakhan State Technical University
Osovsky Alexey V., Astrakhan State Technical University
Abstract: 

The purpose of our study was to formulate provisions for obtaining an integral assessment characterizing the rating of forest areas in terms of fire hazard. We obtained this estimate based on the aggregation of many parameters characterizing climatic conditions and factors that take into account anthropogenic influence in a given area of the forest. Considering the heterogeneity of such parameters, we used the methods of fuzzy inference and the theory of fuzzy sets to aggregate them. The complex for determining the assessment of the forest area is implemented in the form of a hierarchical fuzzy inference system. We investigated the process of functioning of the formed complex and found that its output pattern is predominantly stepwise. This result makes it possible to classify the analyzed forest areas into states groups. Further studies of the classes of states formed by us by the methods of cluster analysis make it possible to identify areas with similar characteristics. The use of the classification results makes it possible to rank forest areas according to the order of preventive or preparatory measures to reduce  fire hazard or increase  responsiveness in case of a fire. The results obtained by us are aimed at using in decision support systems for the management of forests and other types of adjacent territories.

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Received: 
23.03.2022
Accepted: 
01.06.2022
Published: 
01.03.2023