Please use this identifier to cite or link to this item: http://repository.aaup.edu/jspui/handle/123456789/1605
Title: Optimal Centers’ Allocation in Smoothing or Interpolating with Radial Basis Functions
Authors: Idais, Hasan $AAUP$Palestinian
Keywords: approximation; interpolation;
RBFs; centers’ allocation; MOGA; NSGA-II algorithms
Issue Date: 24-Dec-2021
Publisher: MDPI
Citation: 1
Abstract: Function interpolation and approximation are classical problems of vital importance in many science/engineering areas and communities. In this paper, we propose a powerful methodology for the optimal placement of centers, when approximating or interpolating a curve or surface to a data set, using a base of functions of radial type. In fact, we chose a radial basis function under tension (RBFT), depending on a positive parameter, that also provides a convenient way to control the behavior of the corresponding interpolation or approximation method. We, therefore, propose a new technique, based on multi-objective genetic algorithms, to optimize both the number of centers of the base of radial functions and their optimal placement. To achieve this goal, we use a methodology based on an appropriate modification of a non-dominated genetic classification algorithm (of type NSGA-II). In our approach, the additional goal of maintaining the number of centers as small as possible was also taken into consideration. The good behavior and efficiency of the algorithm presented were tested using different experimental results, at least for functions of one independent variable.
URI: http://repository.aaup.edu/jspui/handle/123456789/1605
ISSN: 22277392
Appears in Collections:Faculty & Staff Scientific Research publications

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