A multivariate neural forecasting modeling for air transport – Preprocessed by decomposition: A Brazilian application

K.P.G. Alekseev and J.M. Seixas

Journal of Air Transport Management, 2009, vol. 15, issue 5, 212-216

Abstract: An artificial neural forecasting model is developed for air transport passenger analysis. It uses a preprocessing method that decomposes information to reveal relevant features from the data. It is found that neural processing outperforms the traditional econometric approach and offers generalization on time series behavior, even where there are only small samples.

Keywords: Neural networks; Time series; Air transport; Forecasting; Demand forecasting in air transport passenger (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jaitra:v:15:y:2009:i:5:p:212-216

DOI: 10.1016/j.jairtraman.2008.08.008

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