@inproceedings{926f221e638e42778b72fc6b36548a34,
title = "RBF network combined with wavelet denoising for sardine catches forecasting",
abstract = "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.",
keywords = "Forecasting, Neural networks, Wavelet denoising",
author = "Nibaldo Rodriguez and Broderick Crawford and Eleuterio Ya{\~n}ez",
year = "2008",
language = "English",
isbn = "9789898111524",
series = "ICSOFT 2008 - Proceedings of the 3rd International Conference on Software and Data Technologies",
number = "ABF/-",
pages = "308--311",
booktitle = "ICSOFT 2008 - 3rd International Conference on Software and Data Technologies, Proceedings",
edition = "ABF/-",
note = "3rd International Conference on Software and Data Technologies, ICSOFT 2008 ; Conference date: 05-07-2008 Through 08-07-2008",
}