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Ante la necesidad de predecir a corto plazo la velocidad de viento local, como recurso energtico; surgen un sinfn de procedimientos, cuya finalidad es optimizar la produccin de parques elicos y gestin de las compaas distribuidoras de energa elctrica. Generalmente, utilizan de un modo u otro datos experimentales in situ, obviando el comportamiento no lineal de estas series. Este libro recoge la investigacin encaminada a analizar y predecir el comportamiento de series no lineales, como la velocidad de viento, desde el mbito del "data mining". La metodologa que aqu se propone, interconecta anlisis de wavelets, teora del caos y redes neuronales junto con tcnicas clusters. Experimentalmente, se ha aplicado sobre la velocidad de viento, medida en las instalaciones del Centro de Desarrollo de Energas Renovables del CIEMAT, Centro de Investigaciones Energticas, Medioambientales y Tecnolgicas, adscrito al Ministerio de Economa y Competitivdad. Este estudio es de gran utilidad, a todo aqul que le interese y apasione la prediccin de la velocidad de viento, la energa que produce; y por qu no, la de cualquier otro proceso con comportamiento no lineal.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer,
birth defects, or other reproductive harm.
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