Data science for wind energy / Yu Ding

Von:

Ding, Yu [VerfasserIn]

Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Verlag: Boca Raton : London, [2020]Beschreibung: 1 Online-Ressource : illustrationsISBN:

9780429956508
9780429956515
9780429490972
9780429956492

Schlagwörter:

Andere physische Formen: 9781138590526. | Erscheint auch als: Data science for wind energy. Druck-Ausgabe Boca Raton, Florida : CRC Press, 2020. XXIII, 400 SeitenLOC-Klassifikation:

TJ820

Online-Ressourcen:

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Zusammenfassung: Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy applications, near-ground wind field analysis and forecast, turbine power curve fitting and performance analysis, turbine reliability assessment, and maintenance optimization for wind turbines and wind farms. A broad set of data science methods covered, including time series models, spatio-temporal analysis, kernel regression, decision trees, kNN, splines, Bayesian inference, and importance sampling. More importantly, the data science methods are described in the context of wind energy applications, with specific wind energy examples and case studies. Features Provides an integral treatment of data science methods and wind energy applications Includes specific demonstration of particular data science methods and their use in the context of addressing wind energy needs Presents real data, case studies and computer codes from wind energy research and industrial practice Covers material based on the author's ten plus years of academic research and insightsPPN: PPN: 1685644430Package identifier: Produktsigel: BSZ-4-NLEBK-KAUB | ZDB-4-NLEBK

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