A COMPARISON OF EXPONENTIAL SMOOTHING AND NEURAL NETWORKS IN TIME SERIES PREDICTION

In this article, we compare the accuracy of the forecasts for the exponential smoothing (ES) approach and the radial basis function neural networks (RBFNN) when three nonlinear time series with trend and seasonal cycle are forecasted. In addition, we consider the recommendations of preprocessing by...

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Veröffentlicht in:Dyna
Hauptverfasser: JUAN DAVID VELÁSQUEZ HENAO, CRISTIAN OLMEDO ZAMBRANO PEREZ, CARLOS JAIME FRANCO CARDONA
Format: Artigo
Sprache:Inglês
Veröffentlicht: Universidad Nacional de Colombia 2013
Schlagworte:
Ingeniería
nonlinear models
Forecasts combination
nonlinear time series
artificial neural networks
Online Zugang:https://www.redalyc.org/articulo.oa?id=49629318009
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