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2017 | OriginalPaper | Buchkapitel

40. Object Surface Representation Via NURBS and Genetic Algorithms with SBX

verfasst von : J. Apolinar Muñoz Rodríguez, Francisco Calos Mejia Alanís

Erschienen in: Emerging Challenges for Experimental Mechanics in Energy and Environmental Applications, Proceedings of the 5th International Symposium on Experimental Mechanics and 9th Symposium on Optics in Industry (ISEM-SOI), 2015

Verlag: Springer International Publishing

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Abstract

A technique to represent object surface via NURBS and genetic algorithms is presented. In this technique, the surface is generated based on control points. Then, the control points and the weights are optimized via genetic algorithms to find the NURBS, which represents the object surface. The genetic algorithm is constructed through an objective function, which is deduced from the NURBS surface. This objective function is minimized by using the simulated binary crossover. The proposed genetic algorithm improves accuracy and speed of the NURBS surface representation. The contribution of the proposed method is elucidated by an evaluation based on model accuracy and speed of traditional genetic NURBS surface representation.

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Titel: Object Surface Representation Via NURBS and Genetic Algorithms with SBX
verfasst von: J. Apolinar Muñoz Rodríguez
Francisco Calos Mejia Alanís
Verlag: Springer International Publishing
Buch: Emerging Challenges for Experimental Mechanics in Energy and Environmental Applications, Proceedings of the 5th International Symposium on Experimental Mechanics and 9th Symposium on Optics in Industry (ISEM-SOI), 2015
Print ISBN: 978-3-319-28511-5

Electronic ISBN: 978-3-319-28513-9

Copyright-Jahr: 2017
DOI: https://doi.org/10.1007/978-3-319-28513-9_40

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