Combining the reproducing kernel method with a practical technique to solve the system of nonlinear singularly perturbed boundary value problems

IF 1.1 Q2 MATHEMATICS, APPLIED Computational Methods for Differential Equations Pub Date : 2021-06-20 DOI:10.22034/CMDE.2021.40288.1758
S. Abbasbandy, Hussein Sahihi, T. Allahviranloo
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引用次数: 0

Abstract

In this paper, a reliable new scheme is presented based on combining Reproducing Kernel Method (RKM) with a practical technique for the nonlinear problem to solve the System of Singularly Perturbed Boundary Value Problems (SSPBVP). The Gram-Schmidt orthogonalization process is removed in the present RKM. However, we provide error estimation for the approximate solution and its derivative. Based on the present algorithm in this paper, can also solve linear problem. Several numerical examples demonstrate that the present algorithm does have higher precision.
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将再现核法与实用技术相结合,求解系统的非线性奇摄动边值问题
本文将再现核法(RKM)与一种实用的非线性问题求解技术相结合,提出了一种可靠的奇异摄动边值问题求解方案。在现有的RKM中,去掉了Gram-Schmidt正交化过程。然而,我们提供了近似解及其导数的误差估计。基于本文提出的算法,还可以求解线性问题。算例表明,该算法具有较高的精度。
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来源期刊
CiteScore
2.20
自引率
27.30%
发文量
0
审稿时长
4 weeks
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