Fuzzy modeling of disturbed lands natural revegetation

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Abstract

The problem of disturbed lands recultivation is considered. Since no methodological approach has been developed, the primary task to be solved is to determine the desired period of time for lands natural revegetation. Agrotechnical revegetation measures effectiveness could be compared with the one of natural revegetation only if this task has been solved. The object of this research was the fund of mined disturbed lands in the Sverdlovsk region. All parameters of this object were characterized by data uncertainty conditions, therefore the main idea of the work was to use fuzzy logic, first to describe the main parameters affecting the revegetation process, and then to obtain a functional dependence of the output parameter, i.e. the recovery time period from these initial parameters. Thus, the goal of the research was to develop a fuzzy model of the process of natural revegetation of disturbed lands. The authors studied experimentally the disturbed lands state in a particular region; developed the problem statement; justified fuzzy membership functions of the problem; developed a base of rules for fuzzy products; obtained fuzzy inference and the resulting function; and developed software implementation of the task. The research results were software-implemented in the Scilab environment functional dependence of disturbed lands revegetation period on the type of soil, its parameters and the type of vegetation. The results might be applied to design agrotechnical, regulatory and other measures for disturbed lands revegetation.

About the authors

Vladimir Viktorovich Pobedinskiy

Ural State Forest Engineering University» (Russian Federation)FSBEE HE «Ural State Agrarian University

Email: pobed@e1.ru

Evgeniya Vasilevna Anyanova

Ural State Forestry University

Email: anyanovagv@m.usfeu.ru

Rudolf Nikolaevich Kovalev

Ural State Forest Engineering University» (Russian Federation)FSBEE HE «Ural State Agrarian University

Email: kovalevrn@m.usfeu.ru

Grigory Aleksandrovich Iovlev

Ural State Agrarian University

Email: gri-iovlev@yandex.ru

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Copyright (c) 2022 Pobedinskiy V.V., Anyanova E.V., Kovalev R.N., Iovlev G.A.

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