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Data Science for Wind Energy (Hardcover)
Loot Price: R3,258
Discovery Miles 32 580
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Data Science for Wind Energy (Hardcover)
Expected to ship within 12 - 17 working days
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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. 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
insights
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