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Data Science for Wind Energy

Data Science for Wind Energy

Hardcover

Business GeneralDatabasesProgramming

ISBN10: 1138590525
ISBN13: 9781138590526
Publisher: Crc Pr Inc
Published: May 24 2019
Pages: 400
Weight: 1.75
Height: 1.10 Width: 6.40 Depth: 9.20
Language: English

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. Please also visit the author's book site at https: //aml.engr.tamu.edu/book-dswe.

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Business General