RBF network combined with wavelet denoising for sardine catches forecasting

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

This paper deals with time series of monthly sardines catches in the north area of Chile. The proposed method combines radial basis function neural network (RBFNN) with wavelet denoising algorithm. Wavelet dcnoising is based on stationary wavelet transform with hard thresholding rule and the RBFNN architecture is composed of linear and nonlinear weights, which are estimated by using the separable nonlinear least square method. The performance evaluation of the proposed forecasting model showed that a 93% of the explained variance was captured with a reduced parsimony.

Idioma originalInglés
Título de la publicación alojadaICSOFT 2008 - 3rd International Conference on Software and Data Technologies, Proceedings
Páginas308-311
Número de páginas4
EdiciónABF/-
EstadoPublicada - 2008
Publicado de forma externa
Evento3rd International Conference on Software and Data Technologies, ICSOFT 2008 - Porto, Portugal
Duración: 5 jul. 20088 jul. 2008

Serie de la publicación

NombreICSOFT 2008 - Proceedings of the 3rd International Conference on Software and Data Technologies
NúmeroABF/-
VolumenISDM

Conferencia

Conferencia3rd International Conference on Software and Data Technologies, ICSOFT 2008
País/TerritorioPortugal
CiudadPorto
Período5/07/088/07/08

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