基于算术平均值、均方根和中心平均值线性组合的三阶 Runge-Kutta 方法的混合模糊微分方程数值解法

P. E. D. Rajakumari, R. G. Sharmila
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摘要

目的:本文开发了三阶 Runge-Kutta 方法,该方法使用算术平均数、均方根和中心平均数的线性组合来求解混合模糊微分方程。方法:考虑了 Seikkala 的导数,并提供了一个数值示例来说明所提方法的有效性。结果表明,建议的方法是近似求解混合模糊微分方程的有效工具。研究结果比较分析是使用目前使用的三阶 Runge-Kutta 方法进行的,该方法基于算术平均数、均方根和中心平均数。与其他方法相比,建议的方法提供了更精确的近似值。新颖性:本研究利用 Khattri 公式,将算术平均数、均方根平均数和中心对称平均数三者结合起来,开发出一种新公式。所开发的公式被用于求解一阶混合模糊微分方程的三阶 Runge-Kutta 方法。所有可模拟为初值问题的现实问题都可使用该公式求解。关键词混合模糊微分方程 三角模糊数 Seikkala导数 三阶Runge-Kutta法 算术平均数 均方根 平均值 初始值问题
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Numerical Solution of Hybrid Fuzzy Differential Equation by using Third Order Runge-Kutta Method Based on Linear Combination of Arithmetic Mean, Root Mean Square and Centroidal Mean
Objectives: This article develops the third order Runge-Kutta method, which uses a linear combination of the arithmetic mean, root mean square, and centroidal mean, to solve hybrid fuzzy differential equations. Methods: Seikkala's derivative is taken into account, and a numerical example is provided to show the efficacy of the proposed method. The outcomes demonstrate that the suggested approach is an effective tool for approximating the solution of hybrid fuzzy differential equations. Findings: The comparative analysis was carried out using the third order Runge-Kutta method that is currently in use and is based on arithmetic mean, root mean square, and centroidal mean. Compared to other methods, the suggested method offers a more accurate approximation. Novelty: In this study a new formula has been developed by combining three means Arithmetic Mean, Root Mean Square, and Centroidal Mean using Khattri's formula. And the developed formula is used to solve the third order Runge-Kutta method for the first order hybrid fuzzy differential equation. All real life problems which can be modeled in to an initial value problem can be solved using this formula. Keywords: Hybrid fuzzy differential equations, Triangular fuzzy number, Seikkala's derivative, third order Runge-Kutta method, Arithmetic mean, Root mean square, Centroidal mean, Initial value problem
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