Noisy data fitting with B-splines using hierarchical genetic algorithm

C. H. Garcia-Capulin, G. Trejo-Caballero, H. Rostro-Gonzalez, J. G. Avina-Cervantes

Producción científica: Capítulo del libroContribución a congreso/conferenciarevisión exhaustiva

Resumen

Data fitting by splines in noise presence, has been widely used in data analysis and engineering applications. In this regard, an important problem associated with data fitting by splines is the adequate selection of the number and location of the knots, as well as the calculation of the splines coefficients. Typically, these parameters are separately estimated in the aim of solving this non-linear problem. In this paper, we use a hierarchical genetic algorithm to tackle the data fitting problem by B-splines. The proposed approach is based on a novel hierarchical gene structure for the chromosomal representation, thus, allowing us to determine the number and location of the knots, and the B-spline coefficients automatically and simultaneously. The method is fully based on genetic algorithms and does not require subjective parameters like smooth factor or knot locations to perform the solution. In order to validate the efficacy of the proposed approach, numerical results from tests on smooth functions have been included.

Idioma originalInglés
Título de la publicación alojada23rd International Conference on Electronics, Communications and Computing, CONIELECOMP 2013
Páginas62-66
Número de páginas5
DOI
EstadoPublicada - 2013
Publicado de forma externa
Evento23rd International Conference on Electronics, Communications and Computing, CONIELECOMP 2013 - Cholula, Puebla, México
Duración: 11 mar 201313 mar 2013

Serie de la publicación

Nombre23rd International Conference on Electronics, Communications and Computing, CONIELECOMP 2013

Conferencia

Conferencia23rd International Conference on Electronics, Communications and Computing, CONIELECOMP 2013
País/TerritorioMéxico
CiudadCholula, Puebla
Período11/03/1313/03/13

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