AbstractAn 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.


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    Title :

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


    Contributors:

    Published in:

    Publication date :

    2008-01-01


    Size :

    5 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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