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dc.contributor.authorClaveria, Oscar
dc.contributor.authorMonte Moreno, Enrique
dc.contributor.authorTorra Porras, Salvador
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2014-07-23T06:55:25Z
dc.date.created2014-07-21
dc.date.issued2014-07-21
dc.identifier.citationClaveria, O.; Monte, E.; Torra Porras, S. Tourism demand forecasting with neural network models: different ways of treating information. "International journal of tourism research", 21 Juliol 2014, vol. 17, núm. 3, p. 209-312.
dc.identifier.issn1099-2340
dc.identifier.urihttp://hdl.handle.net/2117/23584
dc.description.abstractThis 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 topologies regarding the number of lags used for concatenation so as to evaluate the effect of the memory on the forecasting results. We find that for higher memories, the forecasting performance obtained for longer horizons improves, suggesting the importance of increasing the dimensionality for long-term forecasting.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació
dc.subject.lcshNeural networks (Computer science)
dc.subject.lcshArtificial intelligence
dc.subject.otherTourism demand
dc.subject.otherForecasting
dc.subject.otherArtificial neural networks
dc.subject.otherMulti-layer perceptron
dc.subject.otherRadial basis function
dc.subject.otherElman networks
dc.titleTourism demand forecasting with neural network models: different ways of treating information
dc.typeArticle
dc.subject.lemacXarxes neuronals (Informàtica)
dc.subject.lemacIntel·ligència artificial
dc.contributor.groupUniversitat Politècnica de Catalunya. VEU - Grup de Tractament de la Parla
dc.identifier.doi10.1002/jtr.2016
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://onlinelibrary.wiley.com/doi/10.1002/jtr.2016/abstract
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac15013651
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
local.citation.authorClaveria, O.; Monte, E.; Torra Porras, S.
local.citation.publicationNameInternational journal of tourism research
local.citation.volume17
local.citation.number3
local.citation.startingPage209
local.citation.endingPage312


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Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain