用新的迭代方法对多物种种群动态模型进行数值模拟

Indranil Ghosh , Muhammad Mahbubur Rashid , Shukranul Mawa
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引用次数: 0

摘要

本研究探讨了Lotka-Volterra多物种种群动态模型,这是一个迷人的非线性数学框架,在自然科学和环境研究中具有重要应用。主要目标是使用新迭代方法(NIM)为这些模型提供精确的解决方案。对三种不同类型的非线性动力学问题进行了数值模拟,比较了NIM与摄动迭代算法(PIA)、现有精确解和传统四阶龙格-库塔法的精度。龙格-库塔法在所有计算中均采用连续步长Δ = 0.001。值得注意的是,非线性多物种Lotka-Volterra模型的NIM解显示出非常好的精度,在5次迭代内实现了与龙格-库塔方法解的收敛。发现NIM的正确性优于其他现有的解决方案。其独特的属性在于其计算效率,在不需要线性化、离散化、乘法器或多项式的情况下提供高精度的非线性项。这导致更简单的解决过程,同时保持值得称赞的准确性。这些发现强调了NIM在线性和非线性模型中的可靠性和广泛适用性,突出了它作为数值计算中宝贵工具的潜力。
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An evaluation of multispecies population dynamics models through numerical simulations using the new iterative method

This study explores the multispecies Lotka-Volterra population dynamics models, a captivating nonlinear mathematical framework with significant applications in natural sciences and environmental studies. The primary objective is to deliver precise solutions for these models using the New Iterative Method (NIM). Numerical simulations are conducted on three distinct types of nonlinear dynamic problems, comparing the accuracy of the NIM with that of the Perturbation Iteration Algorithm (PIA), existing exact solutions, and the traditional fourth-order Runge–Kutta method. A continuous step time of Δ = 0.001 was used for the Runge–Kutta method in all computations. Notably, the NIM's solutions for the nonlinear multispecies Lotka-Volterra models demonstrate very good accuracy, achieving convergence to the Runge–Kutta method's solutions within five iterations. The correctness of the NIM is found to be better than the other existing solutions. Its distinctive attribute lies in its computational efficiency, providing high accuracy without necessitating linearization, discretization, multipliers, or polynomials for nonlinear terms. This leads to simpler solution procedures while maintaining commendable accuracy. The findings underscore NIM's reliability and broad applicability in both linear and nonlinear models, highlighting its potential as an invaluable tool in numerical computation.

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来源期刊
Healthcare analytics (New York, N.Y.)
Healthcare analytics (New York, N.Y.) Applied Mathematics, Modelling and Simulation, Nursing and Health Professions (General)
CiteScore
4.40
自引率
0.00%
发文量
0
审稿时长
79 days
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