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Radial basis function metamodels using factorial and Latin hypercube designs provided better fit than polynomial metamodels using full factorial designs.
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"Metamodeling: Radial basis functions, versus polynomials," European Journal of Operational Research, Elsevier, vol. 138(1), pages 142-154, April. Handle ...
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Jun 15, 2021 · In this paper, an attempt is put forward to investigate the utility of radial basis function (RBF) metamodels in the predictive modelling of laminated ...
May 3, 2016 · This greatly increases the geometric flexibility of the discretizations and makes it easier to carry out local refinement in critical areas.
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In this study, a hybrid metamodel using the orthogonal constraints of radial basis function and sparse polynomial chaos expansions is proposed for the ...
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In this work, four types of metamodeling methods, including multivariate polynomial method, radial basis function method, kriging method and Bayesian neural ...
Uses linear combinations of basis functions, such as linear, cubic, thin-plate spline, Gaussian, multiquadric, and inverse-multiquadric.
One aspect to notice in contrast to polynomials, the accuracy of the interpolation process using splines is not based on the polynomial degree but on the ...
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In this article, a study is performed on the accuracy of radial basis functions (RBFs) in creating global metamodels for both low- and high-order nonlinear ...
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