Application of Radial Basis Function Method for Solving Nonlinear Integral Equations

The radial basis function (RBF) method, especially the multiquadric (MQ) function, was proposed for one- and two-dimensional nonlinear integral equations. The unknown function was firstly interpolated by MQ functions and then by forming the nonlinear algebraic equations by the collocation method. Fi...

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Main Authors: Huaiqing Zhang, Yu Chen, Chunxian Guo, Zhihong Fu
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2014/381908
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spelling doaj-951d6a76a8dd451793b3502268b664982020-11-24T23:58:52ZengHindawi LimitedJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/381908381908Application of Radial Basis Function Method for Solving Nonlinear Integral EquationsHuaiqing Zhang0Yu Chen1Chunxian Guo2Zhihong Fu3The State Key Laboratory of Transmission Equipment and System Safety and Electrical New Technology, Chongqing University, Chongqing 400044, ChinaThe State Key Laboratory of Transmission Equipment and System Safety and Electrical New Technology, Chongqing University, Chongqing 400044, ChinaThe State Key Laboratory of Transmission Equipment and System Safety and Electrical New Technology, Chongqing University, Chongqing 400044, ChinaThe State Key Laboratory of Transmission Equipment and System Safety and Electrical New Technology, Chongqing University, Chongqing 400044, ChinaThe radial basis function (RBF) method, especially the multiquadric (MQ) function, was proposed for one- and two-dimensional nonlinear integral equations. The unknown function was firstly interpolated by MQ functions and then by forming the nonlinear algebraic equations by the collocation method. Finally, the coefficients of RBFs were determined by Newton’s iteration method and an approximate solution was obtained. In implementation, the Gauss quadrature formula was employed in one-dimensional and two-dimensional regular domain problems, while the quadrature background mesh technique originated in mesh-free methods was introduced for irregular situation. Due to the superior interpolation performance of MQ function, the method can acquire higher accuracy with fewer nodes, so it takes obvious advantage over the Gaussian RBF method which can be revealed from the numerical results.http://dx.doi.org/10.1155/2014/381908
collection DOAJ
language English
format Article
sources DOAJ
author Huaiqing Zhang
Yu Chen
Chunxian Guo
Zhihong Fu
spellingShingle Huaiqing Zhang
Yu Chen
Chunxian Guo
Zhihong Fu
Application of Radial Basis Function Method for Solving Nonlinear Integral Equations
Journal of Applied Mathematics
author_facet Huaiqing Zhang
Yu Chen
Chunxian Guo
Zhihong Fu
author_sort Huaiqing Zhang
title Application of Radial Basis Function Method for Solving Nonlinear Integral Equations
title_short Application of Radial Basis Function Method for Solving Nonlinear Integral Equations
title_full Application of Radial Basis Function Method for Solving Nonlinear Integral Equations
title_fullStr Application of Radial Basis Function Method for Solving Nonlinear Integral Equations
title_full_unstemmed Application of Radial Basis Function Method for Solving Nonlinear Integral Equations
title_sort application of radial basis function method for solving nonlinear integral equations
publisher Hindawi Limited
series Journal of Applied Mathematics
issn 1110-757X
1687-0042
publishDate 2014-01-01
description The radial basis function (RBF) method, especially the multiquadric (MQ) function, was proposed for one- and two-dimensional nonlinear integral equations. The unknown function was firstly interpolated by MQ functions and then by forming the nonlinear algebraic equations by the collocation method. Finally, the coefficients of RBFs were determined by Newton’s iteration method and an approximate solution was obtained. In implementation, the Gauss quadrature formula was employed in one-dimensional and two-dimensional regular domain problems, while the quadrature background mesh technique originated in mesh-free methods was introduced for irregular situation. Due to the superior interpolation performance of MQ function, the method can acquire higher accuracy with fewer nodes, so it takes obvious advantage over the Gaussian RBF method which can be revealed from the numerical results.
url http://dx.doi.org/10.1155/2014/381908
work_keys_str_mv AT huaiqingzhang applicationofradialbasisfunctionmethodforsolvingnonlinearintegralequations
AT yuchen applicationofradialbasisfunctionmethodforsolvingnonlinearintegralequations
AT chunxianguo applicationofradialbasisfunctionmethodforsolvingnonlinearintegralequations
AT zhihongfu applicationofradialbasisfunctionmethodforsolvingnonlinearintegralequations
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