Open AccessMethods of assessing the effectiveness of reforestation based on the theory of fuzzy sets
Author(s) -
Aleksandr N. Kuzminov,
Lyudmila V. Sakharova,
Michael B. Stryukov,
V. Zolnikov
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/595/1/012007
Subject(s) - reforestation , computer science , set (abstract data type) , fuzzy logic , variable (mathematics) , basis (linear algebra) , contrast (vision) , data mining , fuzzy set , estimation , machine learning , artificial intelligence , mathematics , systems engineering , environmental science , engineering , agroforestry , mathematical analysis , geometry , programming language
Purpose of the study: development of a new universal fuzzy-multiple methodology that allows assessing the effectiveness of reforestation based on a variable set of indicators, the significance of which is taken into account on the basis of expert assessments, in contrast to existing assessment methods. The systems of fuzzy-logical conclusions, the so-called standard multilevel [0,1] classifiers, were used as a mathematical tool for constructing the assessment methodology. As a result of the implementation of the methodology, an assessment of reforestation in the Rostov region was carried out on the basis of a set of 23 indicators characterizing the dynamics of reforestation, thinning activities, and patrolling of the forest fund in the region. In comparison with the already existing estimation methods, the proposed estimation method has a number of such advantages, such as: simple calculation scheme; when constructing estimates, taking into account a large number of heterogeneous significant indicators that can vary depending on the available statistical material and the characteristics of the specific practical problem being solved; the possibility of varying the weight of the contribution of the studied indicators to the corresponding comprehensive assessment; the possibility of analyzing on its basis the situation in the region under consideration.