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A meshless technique based on the radial basis functions for solving systems of partial differential equations.

Authors :
Nemati, Mehran
Shafiee, Mahmoud
Ebrahimi, Hamideh
Source :
Computational Methods for Differential Equations; 2022, Vol. 10 Issue 2, p526-537, 12p
Publication Year :
2022

Abstract

The radial basis functions (RBFs) methods were first developed by Kansa to approximate partial differential equations (PDEs). The RBFs method is being truly meshfree becomes quite appealing, owing to the presence of distance function, straight-forward implementation, and ease of programming in higher dimensions. Another considerable advantage is the presence of a tunable free shape parameter, contained in most of the RBFs that control the accuracy of the RBFs method. Here, the solution of the two-dimensional system of nonlinear partial differential equations is examined numerically by a Global Radial Basis Functions Collocation Method (GRBFCM). It can work on a set of random or uniform nodes with no need for element connectivity of input data. For the timedependent partial differential equations, a system of ordinary differential equations (ODEs) is derived from this scheme. Like some other numerical methods, a comparison between numerical results with analytical solutions is implemented confirming the efficiency, accuracy, and simple performance of the suggested method. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
23453982
Volume :
10
Issue :
2
Database :
Complementary Index
Journal :
Computational Methods for Differential Equations
Publication Type :
Academic Journal
Accession number :
157759429
Full Text :
https://doi.org/10.22034/cmde.2021.39707.1740