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Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction provides an up-to- date overview on the broad area of wind generation and forecasting, with a focus on the role and need of Machine Learning in this emerging field of knowledge. Various regression models and signal decomposition techniques are presented and analyzed, including least-square, twin support and random forest regression, all with supervised Machine Learning. The specific topics of ramp event prediction and wake interactions are addressed ...

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    • Title: Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction by Harsh S. Dhiman; Dipankar Deb; Valentina Emilia Balas
    • Publisher: Elsevier S & T
    • Print ISBN: 9780128213537, 0128213531
    • eText ISBN: 9780128213674
    • Edition: 2020
    • Format: EPUB eBook
    $125.00
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