论具有一般延迟分布核的单物种模型的稳定性

IF 5.3 1区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Chaos Solitons & Fractals Pub Date : 2024-08-24 DOI:10.1016/j.chaos.2024.115425
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引用次数: 0

摘要

延迟逻辑方程又称哈钦森方程,是一个简单而优雅的模型,常用于捕捉生物学、医学和经济学中复杂现象的关键特征。本文研究了具有一般延迟分布和营养资源恒定流入的单物种逻辑模型的稳定性。我们为正平衡的线性稳定性和霍普夫分岔的发生提供了条件。这些发现是对现有文献的补充,并适用于特定的延迟分布:Uniform 分布、Dirac-delta 分布和 gamma 分布。我们发现,在没有资源流入的情况下,正平衡在短延迟时是稳定的,但随着平均延迟的增加,正平衡会因霍普夫分岔而失去稳定性。根据延迟分布的不同,模型的动态随资源流入而变化:在均匀分布和狄拉克-德尔塔分布中,动态与无资源流入的情况相似,而在伽马分布中,稳定性取决于延迟阶数 p=1,2,3。
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On the stability of a single-species model with a generic delay distribution kernel

The delayed logistic equation, also known as Hutchinson’s equation, is a simple and elegant model commonly used to capture critical features of complex phenomena in biology, medicine, and economics. This paper studies the stability of a single-species logistic model with a general delay distribution and a constant inflow of nutritional resources. We provide conditions for the linear stability of the positive equilibrium and the occurrence of Hopf bifurcation. The findings complement existing literature and are applied to specific delay distributions: Uniform, Dirac-delta, and gamma distributions. Without resource inflow, we find that the positive equilibrium is stable for short delays but loses stability through Hopf bifurcation as the mean delay increases. The model’s dynamics vary with resource inflow based on the delay distribution: in uniform and Dirac-delta distributions, the dynamics are similar to the no-inflow case, whereas for the gamma distribution, stability depends on the delay order p=1,2,3.

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来源期刊
Chaos Solitons & Fractals
Chaos Solitons & Fractals 物理-数学跨学科应用
CiteScore
13.20
自引率
10.30%
发文量
1087
审稿时长
9 months
期刊介绍: Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.
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