Verhulst离散物流增长

Q4 Mathematics Mathematics Magazine Pub Date : 2023-05-23 DOI:10.1080/0025570X.2023.2199676
D. Kalman
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引用次数: 0

摘要

摘要在本科数学课堂上,最常见的离散形式的逻辑增长是由差分方程定义的。虽然这是逻辑微分方程的自然模拟,而且在许多情况下,它产生的结果与连续模型的结果相似,但它也可能导致混沌行为。本文以一种自然的方式导出了一个由Verhulst差分方程定义的替代离散逻辑模型,该模型具有几个值得注意的性质。例如,Verhulst方程具有由连续逻辑曲线给出的闭合形式解,并且从不导致混沌行为。我们对Verhulst方程的开发也为数学建模的公式应用精化周期提供了一个很好的例子。由于这些和其他原因,Verhulst方程应该与上面给出的更熟悉的逻辑差分方程一起在本科生课程中占有一席之地。
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Verhulst Discrete Logistic Growth
Summary In undergraduate mathematics classes, the most common discrete version of logistic growth is defined by the difference equation . While this is a natural analog of the logistic differential equation, and while in many cases it produces results similar to those of the continuous model, it can also give rise to chaotic behavior. This paper derives in a natural way an alternative discrete logistic model, defined by the Verhulst difference equation, with several noteworthy properties. For example the Verhulst equation has closed form solutions given by continuous logistic curves and never leads to chaotic behavior. Our development of the Verhulst equation also provides a beautiful example of the formulation-application-refinement cycle of mathematical modeling. For these and other reasons, the Verhulst equation deserves a place in the undergraduate curriculum alongside the more familiar logistic difference equation given above.
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来源期刊
Mathematics Magazine
Mathematics Magazine Mathematics-Mathematics (all)
CiteScore
0.20
自引率
0.00%
发文量
68
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