Work

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

Year: 2026

Type: article

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.

Source: Operations Research Forum

DOI: 10.1007/s43069-026-00610-9

Authors: Roberto Cavoretto, Alessandra De Rossi, Sandro Lancellotti, Domenico Mezzanotte

Institutions: University of Turin, University of Basilicata, Istituto per le Applicazioni del Calcolo Mauro Picone, National Research Council

Language: English

Topic: Numerical methods in engineering

Subfield: Mechanics of Materials

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,090