| 005 |
20230331093331.0 |
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190206s2019 xxu eng d |
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|bspa |
| 041 |
|aeng |
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1 |aSáenz-Aguirre, Aitor |
| 245 |
10|aArtificial Neural Network Based Reinforcement Learning for Wind Turbine Yaw Control|hDocumento científico MGEP|cAitor Saenz-Aguirre, Ekaitz Zulueta, Unai Fernandez-Gamiz, Javier Lozano, Jose Manuel Lopez-Guede |
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|c2019 |
| 300 |
|a17 p |
| 500 |
|aArgitaratuta/Publicado |
| 500 |
|aAcceso abierto. CC-BY-NC-ND |
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|aZTBES/RVCTI |
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|aInglés |
| 590 |
|aJCR|b2.707|cENERGY & FUELS|dQ3|e56/103|f2018 |
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|aSJR|b0.612|cElectrical and Electronic Engineering|dC1|e157/605|f2018|f2019-06-28 |
| 590 |
|aWeb of Science |
| 590 |
|aScopus |
| 653 |
|aArtículo |
| 653 |
|aAnálisis de datos y ciberseguridad |
| 653 |
|a2018-2019 |
| 700 |
1 |aZulueta, Ekaitz |
| 700 |
1 |aFernández-Gamiz, Unai |
| 700 |
1 |aLozano Silva, Javier |
| 700 |
1 |aLópez-Guede, José Manuel |
| 710 |
|aMondragon Goi Eskola Politeknikoa |
| 710 |
|aEuskal Herriko Unibertsitatea (EHU) |
| 773 |
|tEnergies. Vol. 12. Nº 3. Special Issue: 10 Years Energies - Horizon 2028. 436. January, |
| 856 |
40|uhttp://dx.doi.org/10.3390/en12030436 |
| 856 |
|uhttp://hdl.handle.net/20.500.11984/1166|yTestu osorako sarbidea/Acceso al texto completo / Full text access |
