Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/76069
Title: Nowcasting of wind speed using support vector regression. Experiments with time series from Gran canaria
Authors: Espino, I.
Hernández, M. 
UNESCO Clasification: 120304 Inteligencia artificial
Keywords: Nowcasting
Support Vector Regression
Wind Speed Forecasting
Issue Date: 2011
Journal: Renewable energy and power quality journal 
Abstract: The aim of this paper is to describe and evaluate a proposal for nowcasting wind speed for wind farm locations from historical time series, based on the method of regression by support vectors. To show the improvement over other methods, we used the ANEMOS Project standard evaluation protocol for forecasting against three reference models to compare, referred to a statistical approach: persistence, autoregressive and autoregressive moving average models. The obtained results show a good performance of the proposed method and how beat the classical reference models.
URI: http://hdl.handle.net/10553/76069
ISSN: 2172-038X
DOI: 10.24084/repqj09.428
Source: Renewable Energy and Power Quality Journal [EISSN 2172-038X], v. 1 (9), p. 700-705, (Mayo 2011)
Appears in Collections:Artículos
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