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dc.contributor.authorGonzález Rodelas, Pedro 
dc.contributor.authorIdais, Hasan M. H.
dc.contributor.authorYasin, Mohammed
dc.contributor.authorPasadas Fernández, Miguel 
dc.date.accessioned2022-02-10T10:22:40Z
dc.date.available2022-02-10T10:22:40Z
dc.date.issued2021-12-24
dc.identifier.citationGonzález-Rodelas, P.; Idais, H.M.H.; Yasin, M.; Pasadas, M. Optimal Centers’ Allocation in Smoothing or Interpolating with Radial Basis Functions. Mathematics 2022, 10, 59. [https://doi.org/10.3390/math10010059]es_ES
dc.identifier.urihttp://hdl.handle.net/10481/72771
dc.descriptionThis work was supported by FEDER/Junta de Andalucía-Consejería de Transformación Económica, Industria, Conocimiento y Universidades (Research Project A-FQM-76-UGR20, University of Granada) and by the Junta de Andalucía (Research Group FQM191).es_ES
dc.description.abstractFunction 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.es_ES
dc.description.sponsorshipJunta de Andalucía-Consejería de Transformación Econímica, Industria, Conocimiento y Universidades A-FQM-76-UGR20es_ES
dc.description.sponsorshipUniversidad de Granadaes_ES
dc.description.sponsorshipEuropean Regional Development Fundes_ES
dc.description.sponsorshipJunta de Andalucía FQM191es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsAtribución 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectApproximationes_ES
dc.subjectInterpolationes_ES
dc.subjectRBFses_ES
dc.subjectCenters’ allocationes_ES
dc.subjectMOGAes_ES
dc.subjectNSGA-II algorithmses_ES
dc.titleOptimal Centers’ Allocation in Smoothing or Interpolating with Radial Basis Functionses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.3390/math10010059
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES


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Atribución 3.0 España
Except where otherwise noted, this item's license is described as Atribución 3.0 España