差分进化算法组合突变策略求解刚性常微分方程的近似优化方法

Mendel Pub Date : 2022-12-20 DOI:10.13164/mendel.2022.2.054
Werry Febrianti, K. A. Sidarto, N. Sumarti
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引用次数: 1

摘要

研究了求解刚性常微分方程的简单组合变异微分进化算法的实现。利用带级数展开式的加权残差法逼近刚性常微分方程的解。我们用一般刚性微分方程求解线性和非线性问题。然后,我们还实现了求解刚性常微分方程组的方法。我们发现我们的算法可以以最小的误差逼近刚性常微分方程的精确解,对于我们所选择的每一个序列长度。因此,该近似方法采用简单组合微分演化的优化方法,可以作为求解刚性常微分方程的一个很好的工具。
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An Approximate Optimization Method for Solving Stiff Ordinary Differential Equations With Combinational Mutation Strategy of Differential Evolution Algorithm
This paper examines the implementation of simple combination mutation of differential evolution algorithm for solving stiff ordinary differential equations. We use the weighted residual method with a series expansion to approximate the solutions of stiff ordinary differential equations. We solve the problems from an ordinary stiff differential equation for linear and nonlinear problems. Then, we also implement our method for solving stiff systems of ordinary differential equations. We find that our algorithm can approximate the exact solution of a stiff ordinary differential equation with the smallest error for each length of series that we have chosen. Thus, this approximation method, by using the optimization method of simple combination differential evolution, can be a good tool for solving stiff ordinary differential equations.
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来源期刊
Mendel
Mendel Decision Sciences-Decision Sciences (miscellaneous)
CiteScore
2.20
自引率
0.00%
发文量
7
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