Please use this identifier to cite or link to this item: http://hdl.handle.net/10995/102689
Title: Stochastic sensitivity of quasiperiodic and chaotic attractors of the discrete Lotka–Volterra model
Стохастическая чувствительность квазипериодических и хаотических аттракторов дискретной модели Лотки–Вольтерры
Authors: Belyaev, A. V.
Perevalova, T. V.
Issue Date: 2020
Publisher: Udmurt State University
Citation: Belyaev A. V. Stochastic sensitivity of quasiperiodic and chaotic attractors of the discrete Lotka–Volterra model / A. V. Belyaev, T. V. Perevalova. — DOI 10.35634/2226-3594-2020-55-02 // Izvestiya Instituta Matematiki i Informatiki Udmurtskogo Gosudarstvennogo Universiteta. — 2020. — Vol. 55. — P. 19-32.
Abstract: The aim of the study presented in this article is to analyze the possible dynamic modes of the deterministic and stochastic Lotka–Volterra model. Depending on the two parameters of the system, a map of regimes is constructed. Parametric areas of existence of stable equilibria, cycles, closed invariant curves, and also chaotic attractors are studied. The bifurcations such as the period doubling, Neimark–Sacker and the crisis are described. The complex shape of the basins of attraction of irregular attractors (closed invariant curve and chaos) is demonstrated. In addition to the deterministic system, the stochastic system, which describes the influence of external random influence, is discussed. Here, the key is to find the sensitivity of such complex attractors as a closed invariant curve and chaos. In the case of chaos, an algorithm to find critical lines giving the boundary of a chaotic attractor, is described. Based on the found function of stochastic sensitivity, confidence domains are constructed that allow us to describe the form of random states around a deterministic attractor. © Solid State Technology.All rights reserved.
Keywords: CHAOS
CLOSED INVARIANT CURVE
POPULATION DYNAMICS
STOCHASTIC SENSITIVITY
URI: http://hdl.handle.net/10995/102689
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 85093890670
PURE ID: 13200043
ISSN: 22263594
DOI: 10.35634/2226-3594-2020-55-02
metadata.dc.description.sponsorship: This study was supported by Russian Science Foundation, grant no. 16–11–10098.
RSCF project card: 16-11-10098
Appears in Collections:Научные публикации, проиндексированные в SCOPUS и WoS CC

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