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The Quasi-Optimal Radial Basis Function Collocation Method: A Technical Note
Author(s) -
Juan Zhang,
Mei Sun,
Enran Hou,
Zhaoxing Ma
Publication year - 2021
Publication title -
journal of mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.252
H-Index - 13
eISSN - 2314-4785
pISSN - 2314-4629
DOI - 10.1155/2021/6694369
Subject(s) - mathematics , radial basis function , conical surface , collocation method , spline (mechanical) , collocation (remote sensing) , basis function , mathematical analysis , basis (linear algebra) , thin plate spline , mathematical optimization , geometry , differential equation , spline interpolation , computer science , ordinary differential equation , structural engineering , machine learning , artificial neural network , engineering , statistics , bilinear interpolation
The traditional radial basis function parameter controls the flatness of these functions and influences the precision and stability of approximation solution. The coupled radial basis function, which is based on the infinitely smooth radial basis functions and the conical spline, achieves an accurate and stable numerical solution, while the shape parameter values are almost independent. In this paper, we give a quasi-optimal conical spline which can improve the numerical results. Besides, we consider the collocation points in the Chebyshev-type which improves solution accuracy of the method with no additional computational cost.

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