Results 11 to 20 of about 1,024,930 (374)
Extended Hermite Radial Basis Functions for Sparse Contours Interpolation
IEEE Access, 2020 In this paper, we present an extended Hermite radial basis functions interpolant for surface reconstruction of sparse contours that allows for shape control with interactive constraints.
Deyun Zhong, Liguan Wang, Lin Bi
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Meshless Computational Strategy for Higher Order Strain Gradient Plate Models
Mathematical and Computational Applications, 2022 The present research focuses on the use of a meshless method for the solution of nanoplates by considering strain gradient thin plate theory. Unlike the most common finite element method, meshless methods do not rely on a domain decomposition.
Francesco Fabbrocino +4 more
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Fluids, 2022 Numerical optimization procedures are one of the most powerful approaches with which to support design processes. Their implementation, nevertheless, involves several conceptual and practical complexities.
Ubaldo Cella +4 more
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Performance of Multilayer Perceptron Neural Network Models and Radial-Based Functions in Estimation of Sugar-cane Crop Yield [PDF]
Journal of Agricultural Science and Sustainable Production, 2020 Background and objective: According to the high importance of sustainable crop production in the agro-industry units, intelligent systems such as artificial neural networks should be used to manage farm units.Therefore, the main purpose of this study was
Sina Sharifi +2 more
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Scaling of radial basis functions
IMA Journal of Numerical Analysis, 2023 Abstract This paper studies the influence of scaling on the behavior of radial basis function interpolation. It focuses on certain central aspects, but does not try to be exhaustive. The most important questions are: How does the error of a kernel-based interpolant vary with the scale of the kernel chosen?
Larsson, Elisabeth, Schaback, Robert
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A Fast Solution for the Generalized Radial Basis Functions Interpolant
IEEE Access, 2020 In this paper, we propose a fast solution method of the generalized radial basis functions interpolant for global interpolation. The method can be used to efficiently interpolate large numbers of geometry constraints for implicit surface reconstruction ...
Deyun Zhong, Liguan Wang, Lin Bi
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Global optimization based on active preference learning with radial basis functions
Machine-mediated learning, 2020 This paper proposes a method for solving optimization problems in which the decision-maker cannot evaluate the objective function, but rather can only express a preference such as “this is better than that” between two candidate decision vectors.
A. Bemporad, D. Piga
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Moving-boundary problems solved by adaptive radial basis functions [PDF]
, 2010 The objective of this paper is to present an alternative approach to the conventional level set methods for solving two-dimensional moving-boundary problems known as the passive transport. Moving boundaries are associated with time-dependent problems and
Atluri +42 more
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Radial basis functions-finite differences collocation and a Unified Formulation for bending, vibration and buckling analysis of laminated plates, according to Murakami's zig-zag theory [PDF]
, 2011 In this paper, we propose to use the Murakami's zig-zag theory for the static and vibration analysis of laminated plates, by local collocation with radial basis functions in a finite differences framework.
A.J.M. Ferreira +45 more
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On spherical averages of radial basis functions [PDF]
, 2008 A radial basis function (RBF) has the general form $$s(x)=\sum_{k=1}^{n}a_{k}\phi(x-b_{k}),\quad x\in\mathbb{R}^{d},$$ where the coefficients a 1,…,a n are real numbers, the points, or centres, b 1,…,b n lie in ℝ d , and φ:ℝ d →ℝ is a radially symmetric
A. Edelman +17 more
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