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Ingeniare. Revista chilena de ingeniería

versión On-line ISSN 0718-3305

Resumen

VELASQUEZ, Juan D; OLAYA, Yris  y  FRANCO, Carlos J. TIME SERIES PREDICTION USING SUPPORT VECTOR MACHINES. Ingeniare. Rev. chil. ing. [online]. 2010, vol.18, n.1, pp.64-75. ISSN 0718-3305.  http://dx.doi.org/10.4067/S0718-33052010000100008.

Time series prediction is an important research problem due to its implications in engineering, economics, finance and social sciences. An important topic about this problematic is the development of new models and its comparison with previous approaches in terms of forecast accuracy. Recently, support vector machines (SVM) have been used for time series prediction, but the reported experiences are limited and there are some problems related to its specification. The aim of this paper is to propose a novel technique for estimating some constants of the SVM usually fixed empirically by the modeler. The proposed technique is used to estimate several SVM with the aim of forecast five benchmark time series; the obtained results are compared with the statistics reported in other papers. The proposed method allow us to obtain competitive SVM for the time series forecasted in comparison with the results obtained using other most traditional models.

Palabras clave : Time series; forecasting; artificial neural networks; support vector machines.

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