Regional forecasting with support vector regressions: the case of Spain
Visualitza/Obre
Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/192724
Tipus de documentReport de recerca
Data publicació2015-05-06
Condicions d'accésAccés obert
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Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
This study attempts to assess the forecasting accuracy of Support Vector Regression (SVR) with regard to other Artificial Intelligence techniques based on statistical learning. We use two different neural networks and three SVR models that differ by the type of kernel used. We focus on international tourism demand to all seventeen regions of Spain. The SVR with a Gaussian kernel shows the best forecasting performance. The best predictions are obtained for longer forecast horizons, which suggest the suitability of machine learning techniques for medium and long term forecasting.
Descripció
Working Paper
CitacióClaveria, O.; Monte, E.; Torra Porras, S. "Regional forecasting with support vector regressions: the case of Spain". 2015.
URL repositori externhttp://www.ub.edu/irea/working_papers/2015/201507.pdf
Fitxers | Descripció | Mida | Format | Visualitza |
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Regional Forecasting with Support.pdf | 545,0Kb | Visualitza/Obre |