Resumen

VELASQUEZ HENAO, JUAN DAVID  y  MONTOYA MORENO, SANTIAGO FERNANDO. CONSUMER PRICE INDEX MODELLING USING AN ARTIFICIAL NEURAL NETWORKS-BASED HYBRID MODEL. Dyna rev.fac.nac.minas [online]. 2005, vol.72, n.147, pp.85-93. ISSN 0012-7353.

A new hybrid model is proposed to forecasting the Colombian Consumer Price Index. It’s based on the structural decomposition of the original time series with the aim of remove any easily detected pattern in the data, and in the use of multilayer perceptron to model hidden relationships in the studied time series. The results overcome classical approaches based on Box-Jenkins methodology and conventional neural networks methodology, and encourage the study of this hybrid approach to modelling other time series.

Palabras clave : forecasting methods; costumer price index; neural networks; hybrid methods.

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