Tourism Demand Forecasting with Neural Network Models: Different Ways of Treating Information
Tourism Demand Forecasting with Neural Network Models: Different Ways of Treating Information
About this item
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Author / Creator
Publisher
Bognor Regis: Blackwell Publishing Ltd
Journal title
Language
English
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Publisher
Bognor Regis: Blackwell Publishing Ltd
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Contents
This paper aims to compare the performance of three different artificial neural network techniques for tourist demand forecasting: a multi‐layer perceptron, a radial basis function and an Elman network. We find that multi‐layer perceptron and radial basis function models outperform Elman networks. We repeated the experiment assuming different topol...
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Full title
Tourism Demand Forecasting with Neural Network Models: Different Ways of Treating Information
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Record Identifier
TN_cdi_csuc_recercat_oai_recercat_cat_2072_238196
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_csuc_recercat_oai_recercat_cat_2072_238196
Other Identifiers
ISSN
1099-2340
E-ISSN
1522-1970
DOI
10.1002/jtr.2016
