Abstract
The aim of this paper is to find a model to forecast 1-month ahead monthly anchovy catches using un-decimated multi-scale stationary wavelet transform (USWT) combined with linear autoregressive (AR) method. The original monthly anchovy catches are decomposed into various sub-series employing USWT and then appropriate sub-series are used as inputs to the multi-scale autoregressive (MAR) model. The MAR’s parameters are estimated using the regularized least squares (RLS) method. RLS based forecasting performance was evaluated using determination coefficient and shown that a 99% of the explained variance was captured with a reduced parsimony and high accuracy.
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Rodriguez, N., Castro, C., Duran, O., Yañez, E. (2008). Undecimated Wavelet Based Autoregressive Model for Anchovy Catches Forecasting. In: Gelbukh, A., Morales, E.F. (eds) MICAI 2008: Advances in Artificial Intelligence. MICAI 2008. Lecture Notes in Computer Science(), vol 5317. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88636-5_31
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DOI: https://doi.org/10.1007/978-3-540-88636-5_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88635-8
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