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Tourism time series forecast

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dc.contributor.authorTeixeira, João Paulo
dc.contributor.authorFernandes, Paula Odete
dc.date.accessioned2016-09-06T11:24:22Z
dc.date.available2016-09-06T11:24:22Z
dc.date.issued2015
dc.description.abstractIn this chapter four combinations of input features and the feedforward, cascade forward and recurrent architectures are compared for the task of forecast tourism time series. The input features of the ANNs consist in the combination of the previous 12 months, the index time modeled by two nodes used to the year and month and one input with the daily hours of sunshine (insolation duration). The index time features associated to the previous twelve values of the time series proved its relevance in this forecast task. The insolation variable can improved results with some architectures, namely the cascade forward architecture. Finally, the experimented ANN models/architectures produced a mean absolute percentage error between 4 and 6%, proving the ability of the ANN models based to forecast this time series. Besides, the feedforward architecture behaved better considering validation and test sets, with 4.2% percentage error in test set.pt_PT
dc.identifier.citationTeixeira, João Paulo; Fernandes, P. O. (2015). Tourism time series forecast. In Varajão, João eduardo [et al.] (eds.) Improving Organizational Effectiveness with Enterprise Information Systems. IGI Global. p. 72-87. ISBN 978-1-4666-8368-6pt_PT
dc.identifier.doi10.4018/978-1-4666-8368-6pt_PT
dc.identifier.isbn978-1-4666-8368-6
dc.identifier.urihttp://hdl.handle.net/10198/13187
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherIGI Globalpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.titleTourism time series forecastpt_PT
dc.typebook part
dspace.entity.typePublication
oaire.citation.endPage87pt_PT
oaire.citation.startPage72pt_PT
oaire.citation.titleImproving Organizational Effectiveness with Enterprise Information Systemspt_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.typebookPartpt_PT
relation.isAuthorOfPublication33f4af65-7ddf-46f0-8b44-a7470a8ba2bf
relation.isAuthorOfPublication2269147c-2b53-4d1c-bc1b-f1367d197262
relation.isAuthorOfPublication.latestForDiscovery2269147c-2b53-4d1c-bc1b-f1367d197262

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