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Comparison of artificial neural network architectures in the task of tourism time series forecast

dc.contributor.authorTeixeira, João Paulo
dc.contributor.authorFernandes, Paula Odete
dc.date.accessioned2014-10-09T11:00:26Z
dc.date.available2014-10-09T11:00:26Z
dc.date.issued2012
dc.description.abstractThe authors have been developing several models based on artificial neural networks, linear regression models, Box-Jenkins methodology and ARIMA models to predict the time series of tourism. The time series consist in the “Monthly Number of Guest Nights in the Hotels” of one region. Several comparisons between the different type models have been experimented as well as the features used at the entrance of the models. The Artificial Neural Network (ANN) models have always had their performance at the top of the best models. Usually the feed-forward architecture was used due to their huge application and results. In this paper the author made a comparison between different architectures of the ANNs using simply the same input. Therefore, the traditional feed-forward architecture, the cascade forwards, a recurrent Elman architecture and a radial based architecture were discussed and compared based on the task of predicting the mentioned time series.por
dc.identifier.citationTeixeira, João Paulo; Fernandes, Paula O. (2012). Comparison of artificial neural network architectures in the task of tourism time series forecast. World Academy of Science, Engineering and Technology (WASET). 66, p 978–983por
dc.identifier.urihttp://hdl.handle.net/10198/10765
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherWorld Academy of Science - Engineering and Technologypor
dc.subjectArtificial neural network architecturespor
dc.subjectTime series forecastpor
dc.subjectTourismpor
dc.titleComparison of artificial neural network architectures in the task of tourism time series forecastpor
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage983por
oaire.citation.startPage978por
oaire.citation.titleWorld Academy of Science, Engineering and Technologypor
oaire.citation.volume66por
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.rightsrestrictedAccesspor
rcaap.typearticlepor
relation.isAuthorOfPublication33f4af65-7ddf-46f0-8b44-a7470a8ba2bf
relation.isAuthorOfPublication2269147c-2b53-4d1c-bc1b-f1367d197262
relation.isAuthorOfPublication.latestForDiscovery2269147c-2b53-4d1c-bc1b-f1367d197262

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