人口动态多维数学模型的综合与分析

A. V. Demidova, O. Druzhinina, M. Jaćimović, O. Masina, N. Mijajlović
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引用次数: 2

摘要

描述了考虑竞争与共生关系的多维种群动态模型的设计。考虑了三维和四维情况下的模型实例,对确定性模型进行了定性和数值研究。用常非线性微分方程组给出了各模型的确定性描述。将其转换为由微分包体、模糊和随机微分方程定义的多维不确定性模型,并进行稳定性分析。综合了“竞争对手-竞争对手-互惠主义者”和“竞争对手-互惠主义者-竞争对手-互惠主义者”的随机模型。描述了具有竞争和互惠的多维随机模型的结构,写出了Fokker-Planck方程,给出了向Langevin形式的随机多维微分方程过渡的规则。对确定性模型和随机模型进行了对比分析。利用开发的龙格-库塔随机方法微分方程组数值解软件包,对所研究的模型进行了数值实验。采用了维纳过程轨迹生成算法和多点分布算法以及龙格-库塔随机方法的数值算法。在许多情况下的数值实验表明,随机和确定性动力学模型的轨迹显著接近。在这种情况下,随机因素的引入对系统的稳定性影响很小,因此可以考虑用确定性方法来研究系统。
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Synthesis and Analysis of Multidimensional Mathematical Models of Population Dynamics
The designing of multidimensional models of population dynamics taking into account the relations of competition and mutualism is described. The model examples in three-dimensional and four-dimensional cases are considered, qualitative and numerical investigation of deterministic models is carried out. The deterministic description of each model is given by the system of ordinary nonlinear differential equations. The transition to the corresponding multidimensional nondeterministic models defined by differential inclusions, fuzzy and stochastic differential equations is made, and stability analysis is performed. Synthesis of the stochastic models “competitor-competitor-mutualist” and “competitor-mutualist-competitor-mutualist” is carried out. The structure of multidimensional stochastic models with competition and mutualism is described, Fokker-Planck equations are written, the rules of the transition to stochastic multidimensional differential equations in the Langevin form are formulated. The comparative analysis of deterministic and stochastic models is carried out. The numerical experiment for the studied models has been carried out with the help of the developed software package for the numerical solution of the differential equations systems by Runge-Kutta stochastic methods. Algorithms for generating trajectories of the Wiener process and multipoint distributions and numerical algorithms of Runge-Kutta stochastic method are used. The numerical experiment in a number of cases showed a significant proximity of stochastic and deterministic dynamic models trajectories. The conditions under which the introduction of stochastics influences poorly the stability of the system and it is possible to consider its deterministic approach for the system studying.
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