Resumen
In this paper, an interpolation neural network is introduced for the learning of a wind turbine behavior with incomplete data. The proposed hybrid method is the combination of an interpolation algorithm and a neural network. The interpolation algorithm is applied to estimate the missing data of all the variables; later, the neural network is employed to learn the output behavior. The proposed method avoids the requirement to know all the system data. Experiments show the effectiveness of the proposed technique.
Idioma original | Inglés |
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Páginas (desde-hasta) | 2017-2028 |
Número de páginas | 12 |
Publicación | Neural Computing and Applications |
Volumen | 28 |
N.º | 8 |
DOI | |
Estado | Publicada - 1 ago. 2017 |