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Modelling tourism demand to Spain with machine learning techniques. The impact of forecast horizon on model selection
dc.contributor.author | Claveria, Oscar |
dc.contributor.author | Torra Porras, Salvador |
dc.contributor.author | Monte Moreno, Enrique |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions |
dc.date.accessioned | 2017-01-27T14:17:34Z |
dc.date.available | 2017-01-27T14:17:34Z |
dc.date.issued | 2016-12-01 |
dc.identifier.citation | Claveria, O., Torra Porras, S., Monte, E. Modelling tourism demand to Spain with machine learning techniques. The impact of forecast horizon on model selection. "Revista de economía aplicada", 1 Desembre 2016, vol. 24, núm. 72, p. 109-132. |
dc.identifier.issn | 1413-8050 |
dc.identifier.uri | http://hdl.handle.net/2117/100218 |
dc.description.abstract | This study assesses the influence of the forecast horizon on the forecasting performance of several machine learning techniques. We compare the fo recastaccuracy of Support Vector Regression (SVR) to Neural Network (NN) models, using a linear model as a benchmark. We focus on international tourism demand to all seventeen regions of Spain. The SVR with a Gaussian radial basis function kernel outperforms the rest of the models for the longest forecast horizons. We also find that machine learning methods improve their forecasting accuracy with respect to linear models as forecast horizons increase. This results shows the suitability of SVR for medium and long term forecasting. |
dc.format.extent | 24 p. |
dc.language.iso | eng |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Ensenyament i aprenentatge::Metodologies docents |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic |
dc.subject.lcsh | Machine learning |
dc.subject.other | Forecasting |
dc.subject.other | Tourism demand |
dc.subject.other | Spain |
dc.subject.other | Support vector regression |
dc.subject.other | Neural networks |
dc.subject.other | Machine learning |
dc.title | Modelling tourism demand to Spain with machine learning techniques. The impact of forecast horizon on model selection |
dc.type | Article |
dc.subject.lemac | Aprenentatge automàtic |
dc.contributor.group | Universitat Politècnica de Catalunya. VEU - Grup de Tractament de la Parla |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://www.revecap.com/revista/ |
dc.rights.access | Open Access |
local.identifier.drac | 19354521 |
dc.description.version | Postprint (published version) |
local.citation.author | Claveria, O.; Torra Porras, S.; Monte, E. |
local.citation.publicationName | Revista de economía aplicada |
local.citation.volume | 24 |
local.citation.number | 72 |
local.citation.startingPage | 109 |
local.citation.endingPage | 132 |
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