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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Series: | Journal of Applied Mathematics |
Online Access: | http://dx.doi.org/10.1155/2014/381908 |
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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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1725449275883651072 |