03120cam a2200565Ii 45000010014000000030008000140050017000220060019000390070015000580080041000730400035001140200035001490200032001840200035002160200032002510200035002830200032003180200035003500200032003850200018004170200015004350350022004500350024004720500021004960720025005170720025005420720025005670720025005920720015006170820024006320820015006561000059006712450045007302640037007753000039008123360026008513370026008773380036009035201105009395880047020446500037020916500033021286500051021616500047022126500033022596500071022928560072023638560102024359990017025379780429490972FlBoTFG20260210180854.0m     o  d        cr cnu---unuuu190607s2020    flu     ob    001 0 eng d  aOCoLC-PbengerdaepncOCoLC-P  a9780429490972qelectronic book  a0429490976qelectronic book  a9780429956508qelectronic book  a0429956509qelectronic book  a9780429956515qelectronic book  a0429956517qelectronic book  z9780429956492qelectronic book  z0429956495qelectronic book  z9781138590526  z1138590525  a(OCoLC)1103917723  a(OCoLC-P)1103917723 4aTJ820b.D56 2020 7aTECx0090702bisacsh 7aBUSx0610002bisacsh 7aCOMx0000002bisacsh 7aCOMx0120402bisacsh 7aUN2bicssc04a621.31/2136028522304a621.452231 aDing, Yuc(Electrical and Computer Engineer),eauthor.10aData science for wind energy /cYu Ding. 1aBoca Raton :bCRC Press,c[2020]  a1 online resource :billustrations  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  aData 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 insights  aOCLC-licensed vendor bibliographic record. 0aWind powerxMathematical models. 0aWind powerxData processing. 7aTECHNOLOGY & ENGINEERING / Mechanical2bisacsh 7aBUSINESS & ECONOMICS / Statistics2bisacsh 7aCOMPUTERS / General2bisacsh 7aCOMPUTERS / Computer Graphics / Game Programming & Design2bisacsh403Taylor & Francisuhttps://www.taylorfrancis.com/books/9780429490972423OCLC metadata license agreementuhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf  c93140d93139