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Numerical Stochastic Simulation of Spatially Heterogeneous Population Full article

Journal Numerical Analysis and Applications
ISSN: 1995-4239
Output data Year: 2024, Volume: 17, Number: 2, Pages: 174-187 Pages count : 14 DOI: 10.1134/s1995423924020071
Tags population dynamics, compartmental system, oriented graph, branching random process, queuing system, Poisson distribution, Monte Carlo method, computational experiment.
Authors Pertsev N.V. 1 , Topchii V.A. 1 , Loginov K.K. 1
Affiliations
1 Sobolev Institute of Mathematics, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia

Funding (1)

1 Омский филиал ФГБУН «Институт математики им. С.Л. Соболева СО РАН». FWNF-2022-0003

Abstract: A continuous-discrete stochastic model is constructed to describe the evolution of a spatially heterogeneous population. The population structure is defined in terms of a graph with two vertices and two unidirectional edges. The graph describes the presence of individuals in the population at the vertices and their transitions between the vertices along the edges. Individuals enter the population to each of the vertices of the graph from an external source. The duration of the migration of individuals along the edges of the graph is constant. Individuals may die or turn into individuals of other populations not considered in the model. The assumptions of the model are formulated, and a probabilistic formalization of the model and a numerical simulation algorithm based on the Monte Carlo method are given. The laws of population size distribution are studied. The results of a computational experiment are presented.
Cite: Pertsev N.V. , Topchii V.A. , Loginov K.K.
Numerical Stochastic Simulation of Spatially Heterogeneous Population
Numerical Analysis and Applications. 2024. V.17. N2. P.174-187. DOI: 10.1134/s1995423924020071 WOS Scopus РИНЦ OpenAlex
Original: Перцев Н.В. , Топчий В.А. , Логинов К.К.
Численное стохастическое моделирование пространственно неоднородной популяции
Сибирский журнал вычислительной математики. 2024. Т.27. №2. С.217-232. DOI: 10.15372/SJNM20240207 РИНЦ OpenAlex
Dates:
Submitted: Feb 9, 2024
Accepted: Mar 4, 2024
Published print: May 28, 2024
Published online: May 28, 2024
Identifiers:
Web of science: WOS:001234788900007
Scopus: 2-s2.0-85194577069
Elibrary: 67307252
OpenAlex: W4399122959
Citing: Пока нет цитирований
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