Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/76069
Título: Nowcasting of wind speed using support vector regression. Experiments with time series from Gran canaria
Autores/as: Espino, I.
Hernández, M. 
Clasificación UNESCO: 120304 Inteligencia artificial
Palabras clave: Nowcasting
Support Vector Regression
Wind Speed Forecasting
Fecha de publicación: 2011
Publicación seriada: Renewable energy and power quality journal 
Resumen: 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
Fuente: Renewable Energy and Power Quality Journal [EISSN 2172-038X], v. 1 (9), p. 700-705, (Mayo 2011)
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