Títol:
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Modelling cross-dependencies between Spain's regional tourism markets with an extension of the Gaussian process regression model
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Autor/a:
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Clavería González, Óscar; Monte Moreno, Enric; Torra Porras, Salvador
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Altres autors:
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Universitat de Barcelona |
Abstract:
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This study presents an extension of the Gaussian process regression model for multiple-input multiple-output forecasting. This approach allows modelling the cross-dependencies between a given set of input variables and generating a vectorial prediction. Making use of the existing correlations in international tourism demand to all seventeen regions of Spain, the performance of the proposed model is assessed in a multiple-step-ahead forecasting comparison. The results of the experiment in a multivariate setting show that the Gaussian process regression model significantly improves the forecasting accuracy of a multi-layer perceptron neural network used as a benchmark. The results reveal that incorporating the connections between different markets in the modelling process may prove very useful to refine predictions at a regional level. |
Matèries:
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-Turisme -Anàlisi de regressió -Processos gaussians -Xarxes neuronals (Informàtica) -Tourism -Regression analysis -Gaussian processes -Neural networks (Computer science) |
Drets:
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(c) Springer Verlag, 2016
info:eu-repo/semantics/embargoedAccess |
Tipus de document:
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Article Article - Versió acceptada |
Publicat per:
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Springer Verlag
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