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) |
Colección: | Artículos |
Citas SCOPUSTM
4
actualizado el 15-dic-2024
Visitas
141
actualizado el 14-dic-2024
Descargas
143
actualizado el 14-dic-2024
Google ScholarTM
Verifica
Altmetric
Comparte
Exporta metadatos
Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.