Numerical Stochastic Simulation of Spatially Heterogeneous Population

IF 0.4 Q4 MATHEMATICS, APPLIED
N. V. Pertsev, V. A. Topchii, K. K. Loginov
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引用次数: 0

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.

Abstract Image

空间异质性种群的数值随机模拟
摘要 建立了一个连续-离散随机模型来描述空间异质种群的演化。种群结构用一个具有两个顶点和两条单向边的图来定义。该图描述了种群中位于顶点的个体及其沿边在顶点之间的转换。个体从外部来源进入种群,到达图中的每个顶点。个体沿图边迁移的时间是恒定的。个体可能会死亡或变成模型中未考虑的其他种群的个体。提出了模型的假设条件,并给出了模型的概率形式化和基于蒙特卡罗方法的数值模拟算法。研究了种群数量分布的规律。介绍了计算实验的结果。
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来源期刊
Numerical Analysis and Applications
Numerical Analysis and Applications MATHEMATICS, APPLIED-
CiteScore
1.00
自引率
0.00%
发文量
22
期刊介绍: Numerical Analysis and Applications is the translation of Russian periodical Sibirskii Zhurnal Vychislitel’noi Matematiki (Siberian Journal of Numerical Mathematics) published by the Siberian Branch of the Russian Academy of Sciences Publishing House since 1998. The aim of this journal is to demonstrate, in concentrated form, to the Russian and International Mathematical Community the latest and most important investigations of Siberian numerical mathematicians in various scientific and engineering fields. The journal deals with the following topics: Theory and practice of computational methods, mathematical physics, and other applied fields; Mathematical models of elasticity theory, hydrodynamics, gas dynamics, and geophysics; Parallelizing of algorithms; Models and methods of bioinformatics.
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