%0 Journal Article
%T Pron¨®stico de series de tiempo con tendencia y ciclo estacional usando el modelo airline y redes neuronales artificiales
%A Vel¨¢squez
%A J. D
%A Franco
%A C. J
%J Ingenier¨ªa y Ciencia
%D 2012
%I Universidad EAFIT
%X many time series with trend and seasonal pattern are successfully modeled and forecasted by the airline model of box and jenkins; however, this model neglects the presence of nonlinearity on data. in this paper, we propose a new nonlinear version of the airline model; for this, we replace the moving average linear component by a multilayer perceptron neural network. the proposed model is used for forecasting two benchmark time series; we found that the proposed model is able to forecast the time series with more accuracy that other traditional approaches.
%K prediction
%K nonlinear macroeconomics
%K sarima
%K multilayer perceptrons.
%U http://www.scielo.org.co/scielo.php?script=sci_abstract&pid=S1794-91652012000100009&lng=en&nrm=iso&tlng=en