What question did this study set out to answer?

The aim is to determine the optimal shape parameter for radial basis function interpolation using a genetic algorithm.

February 19, 2026Open Access

Genetic Algorithm-Based Shape Parameter Tuning for Radial Basis Function Interpolation

Key Points

The aim is to determine the optimal shape parameter for radial basis function interpolation using a genetic algorithm.
Utilized a genetic algorithm inspired by evolutionary selection for optimization.
Conducted numerical experiments to validate the approach.
Compared outcomes with standard leave-one-out cross-validation method.
The genetic algorithm successfully identified optimal shape parameters.
Demonstrated improved computational efficiency compared to traditional methods.

Abstract

Abstract In this study, we address the non-trivial problem of determining the optimal shape parameter in radial basis function interpolation. We propose the use of a genetic algorithm, an optimization technique inspired by evolutionary selection, to identify this parameter. Numerical experiments are presented to evaluate the effectiveness of this approach, with direct comparisons to the leave-one-out cross-validation method, thereby highlighting its computational efficiency.

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Authors

Roberto Cavoretto

Alessandra De Rossi

Sandro Lancellotti

Journals

Operations Research Forum

Actions

Institutions

University of Turin

University of Basilicata

Collegio Carlo Alberto

References and Citations

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Building similarity graph...

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Genetic Algorithm-Based Shape Parameter Tuning for Radial Basis Function Interpolation

Key Points

Abstract

Citation Network

Connected Papers

Discussion

Authors

Journals

Actions

Institutions

References and Citations

Citation Network

Connected Papers

Discussion

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