2020
DOI: 10.1155/2020/6664071
|View full text |Cite
|
Sign up to set email alerts
|

The Conical Radial Basis Function for Partial Differential Equations

Abstract: The performance of the parameter-free conical radial basis functions accompanied with the Chebyshev node generation is investigated for the solution of boundary value problems. In contrast to the traditional conical radial basis function method, where the collocation points are placed uniformly or quasi-uniformly in the physical domain of the boundary value problems in question, we consider three different Chebyshev-type schemes to generate the collocation points. This simple scheme improves accuracy of the me… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2021
2021
2023
2023

Publication Types

Select...
3

Relationship

1
2

Authors

Journals

citations
Cited by 3 publications
(1 citation statement)
references
References 21 publications
0
1
0
Order By: Relevance
“…As is known to all, the selection of shape parameter in the traditional MQ-RBF is very important in dealing with partial differential equations, and its small variation may cause severe differences to solutions [2]. e selection of optimal shape parameter in the RBF methods has long been a challenging task [3][4][5][6][7]. Several attempts and considerable progress have been made in literatures [8][9][10][11], but this question still remains a bottleneck for the MQ method application to practical problems.…”
Section: Introductionmentioning
confidence: 99%
“…As is known to all, the selection of shape parameter in the traditional MQ-RBF is very important in dealing with partial differential equations, and its small variation may cause severe differences to solutions [2]. e selection of optimal shape parameter in the RBF methods has long been a challenging task [3][4][5][6][7]. Several attempts and considerable progress have been made in literatures [8][9][10][11], but this question still remains a bottleneck for the MQ method application to practical problems.…”
Section: Introductionmentioning
confidence: 99%