Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/90304
Title: The stochastic sensitivity function method in analysis of the piecewise-smooth model of population dynamics
Authors: Belyaev, A. V.
Ryazanova, T. V.
Issue Date: 2019
Publisher: Udmurt State University
Citation: Belyaev, A. V. The stochastic sensitivity function method in analysis of the piecewise-smooth model of population dynamics / A. V. Belyaev, T. V. Ryazanova. — DOI 10.20537/2226-3594-2019-53-04 // Izvestiya Instituta Matematiki i Informatiki Udmurtskogo Gosudarstvennogo Universiteta. — 2019. — Iss. 53. — P. 36-47.
Abstract: This work is devoted to the application of the stochastic sensitivity function method to attractors of a piecewise-smooth one-dimensional map describing the dynamics of the population size. The first stage of the study is a parametric analysis of possible modes of the deterministic model: the definition of zones of existence of stable equilibria and chaotic attractors. The theory of critical points is used to determine the parametric boundaries of a chaotic attractor. In the case where the system is influenced by a random effect, based on the technique of the stochastic sensitivity function, a description of the spread of random states around the equilibrium and chaotic attractor is carried out. A comparative analysis of the influence of parametric and additive noise on the attractors of the system is conducted. Using the technique of confidence intervals, probabilistic mechanisms of extinction of a population under the influence of random disturbances are studied. Changes in the parametric boundaries of the existence of a population under the impact of a random perturbation are analyzed. © 2019 Udmurt State University. All right reserved.
Keywords: PIECEWISE-SMOOTH MAP
POPULATION DYNAMICS
STOCHASTIC SENSITIVITY
URI: http://elar.urfu.ru/handle/10995/90304
Access: info:eu-repo/semantics/openAccess
RSCI ID: 38503197
SCOPUS ID: 85079116293
WOS ID: 000487290700004
PURE ID: 10353519
ISSN: 2226-3594
DOI: 10.20537/2226-3594-2019-53-04
Sponsorship: Russian Science Foundation, RSF: 16–11–10098
Funding. The research was supported by the Russian Science Foundation (project no. 16–11–10098).
RSCF project card: 16-11-10098
Appears in Collections:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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