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Combination forecasts of tourism demand with machine learning models

Autor
Claveria, O.; Monte, E.; Torra Porras, Salvador
Tipus d'activitat
Article en revista
Revista
Applied economics letters
Data de publicació
2015-09-11
Volum
23
Número
6
Pàgina inicial
428
Pàgina final
431
DOI
https://doi.org/10.1080/13504851.2015.1078441 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/83765 Obrir en finestra nova
URL
http://www.tandfonline.com/doi/abs/10.1080/13504851.2015.1078441?journalCode=rael20 Obrir en finestra nova
Resum
The main objective of this study is to analyse whether the combination of regional predictions generated with machine learning (ML) models leads to improved forecast accuracy. With this aim, we construct one set of forecasts by estimating models on the aggregate series, another set by using the same models to forecast the individual series prior to aggregation, and then we compare the accuracy of both approaches. We use three ML techniques: support vector regression, Gaussian process regression ...
Citació
Claveria, O., Monte, E., Torra, S. Combination forecasts of tourism demand with machine learning models. "Applied economics letters", 11 Setembre 2015, vol. 23, núm. 6, p. 428-431.
Paraules clau
Forecast combination, Gaussian process regression, machine learning, neural networks, support vector regression
Grup de recerca
IDEAI-UPC Intelligent Data Science and Artificial Intelligence
TALP - Centre de Tecnologies i Aplicacions del Llenguatge i la Parla
VEU - Grup de Tractament de la Parla

Participants