Short-term wind power forecast based on cluster analysis and artificial neural networks
| Data(s) |
18/07/2016
18/07/2016
2011
|
|---|---|
| Resumo |
<p>[EN]In this paper an architecture for an estimator of short-term wind farm power is proposed. The estimator is made up of a Linear Machine classifier and a set of k Multilayer Perceptrons, training each one for a specific subspace of the input space. The splitting of the input dataset into the k clusters is done using a k-means technique, obtaining the equivalent Linear Machine classifier from the cluster centroids...</p> |
| Identificador |
http://hdl.handle.net/10553/17887 728068 <p><a href="http://dx.doi.org/10.1007/978-3-642-21501-8_24" target="_blank">10.1007/978-3-642-21501-8_24</a></p> |
| Idioma(s) |
eng |
| Direitos |
info:eu-repo/semantics/openAccess |
| Fonte |
<p>Advances in Computational Intelligence. Berlin: Springer, 2011 (Lecture Notes in Computer Science, ISSN 0302-9743; vol. 6691; pp 191-198). ISBN 978-3-642-21500-1. ISBN on-line 978-3-642-21501-8</p> |
| Palavras-Chave | #120304 Inteligencia artificial |
| Tipo |
info:eu-repo/semantics/conferenceObject |
