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In this paper, a Legendre neural network (LNN) combined with multi-scale stationary wavelet decomposition is used to improve the prediction accuracy and parsimony of monthly anchovy catches forecasting in area north of Chile. The general idea behind this approach is to decompose the observed anchovy catches data into low frequency (LF) component and high frequency (HF) component using the multi-scale...
This paper deals with forecasting of monthly sardines catches in north area of Chile. The forecasting model is based on un-decimated stationary wavelet transform (SWT) combined with radial basis function (RBF) neural network and linear autoregressive (AR) model. The original monthly sardines catches data are decomposed into two sub-series employing 1-level SWT and the appropriate subseries are used...
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