Data pre-processing for neural network-based forecasting: does it really matter?
Data pre-processing for neural network-based forecasting: does it really matter?
About this item
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Author / Creator
Publisher
Taylor & Francis
Journal title
Language
English
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Publisher
Taylor & Francis
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Scope and Contents
Contents
This study aims to analyze the effects of data pre-processing on the forecasting performance of neural network models. We use three different Artificial Neural Networks techniques to predict tourist demand: multi-layer perceptron, radial basis function and the Elman neural networks. The structure of the networks is based on a multiple-input multipl...
Alternative Titles
Full title
Data pre-processing for neural network-based forecasting: does it really matter?
Authors, Artists and Contributors
Author / Creator
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Record Identifier
TN_cdi_csuc_recercat_oai_recercat_cat_2072_260369
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_csuc_recercat_oai_recercat_cat_2072_260369
Other Identifiers
ISSN
2029-4913
E-ISSN
2029-4921
DOI
10.3846/20294913.2015.1070772
