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Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/62346
Regional Forecasting with Support Vector Regressions: The Case of Spain
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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.
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CLAVERÍA GONZÁLEZ, Óscar, MONTE MORENO, Enric and TORRA PORRAS, Salvador. Regional Forecasting with Support Vector Regressions: The Case of Spain. IREA – Working Papers. 2015. Vol. IR15/07. ISSN 2014-1254. [consulted: 11 of August of 2026]. Available at: https://hdl.handle.net/2445/62346