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Ingeniería y Ciencia
versão impressa ISSN 1794-9165
Resumo
VELASQUEZ, J. D e FRANCO, C. J. Forecasting of time series with trend and seasonal cycle using the airline model and artificial neural networks. ing.cienc. [online]. 2012, vol.8, n.15, pp.171-189. ISSN 1794-9165.
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.
Palavras-chave : prediction; nonlinear macroeconomics; SARIMA; multilayer perceptrons.