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Tourism time series forecast with artificial neural networks

dc.contributor.authorTeixeira, João Paulo
dc.contributor.authorFernandes, Paula Odete
dc.date.accessioned2018-04-09T15:51:33Z
dc.date.available2018-04-09T15:51:33Z
dc.date.issued2014
dc.description.abstractThe modulation of tourism time series was used in this work for forecast purposes. The Tourism Revenue and Total Overnights registered in the hotels of the North region of Por- tugal were used for the experimented models. Several feed-forward Artificial Neural Networks (ANN) models using different input features and number of hidden nodes were experimented to forecast the Tourism time series. Empirical results indicate that the Dedicated ANN models perform better than models with several outputs. Generally the usage of previous 12 values of the same time series is very important to a good quality forecast. For the prediction of Tourism Revenue the Foreign Overnights and GDP of contributing countries are relevant. This time series was predicted with an error of 4.7% and a Pearson correlation of 0.98. The forecast of Total Overnights had an error of 6.0% and Pearson correlation of 0.98. Domestic Overnights are more predictable than Foreign Overnights.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationTeixeira, João Paulo; Fernandes, Paula O. (2014). Tourism time series forecast with artificial neural networks. Tékhne, Review of Applied Management Studies. ISSN 1645-9911. 12:1-2, p. 26–36pt_PT
dc.identifier.doi10.1016/j.tekhne.2014.08.001pt_PT
dc.identifier.issn1645-9911
dc.identifier.urihttp://hdl.handle.net/10198/16829
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.titleTourism time series forecast with artificial neural networkspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage36pt_PT
oaire.citation.issue1-2pt_PT
oaire.citation.startPage26pt_PT
oaire.citation.titleTékhne, Review of Applied Management Studiespt_PT
oaire.citation.volume12pt_PT
person.familyNameTeixeira
person.familyNameFernandes
person.givenNameJoão Paulo
person.givenNamePaula Odete
person.identifier663194
person.identifierN-3804-2013
person.identifier.ciencia-id4F15-B322-59B4
person.identifier.ciencia-id991D-9D1E-D67D
person.identifier.orcid0000-0002-6679-5702
person.identifier.orcid0000-0001-8714-4901
person.identifier.ridN-6576-2013
person.identifier.scopus-author-id57069567500
person.identifier.scopus-author-id35200741800
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication33f4af65-7ddf-46f0-8b44-a7470a8ba2bf
relation.isAuthorOfPublication2269147c-2b53-4d1c-bc1b-f1367d197262
relation.isAuthorOfPublication.latestForDiscovery33f4af65-7ddf-46f0-8b44-a7470a8ba2bf

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