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100   $a20120921d2012      ua             0
101 0 $aeng
135   $aurcn|||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aWind power plant prediction by using neural networks$b[electronic resource] $epreprint /$fZ. Liu ... [and others]
210  1$a[Golden, Colo.] :$cNational Renewable Energy Laboratory,$d[2012]
215   $a1 online resource (7) $ccolor illustrations
225 1 $aNREL/CP ;$v5500-55871
300   $aTitle from title screen (viewed on Sept. 21, 2012).
300   $a"To be presented at the IEEE Energy conversion Conference and Exposition, Raleigh, North Carolina, September 15-20, 2012."
300   $a"August 2012."
300   $a"Contract No. DE-AC36-08GO28308."
320   $aIncludes bibliographical references (page 7).
517   $aWind power plant prediction by using neural networks 
606   $aWind power$xForecasting
606   $aWind power plants$xForecasting
606   $aNeural networks (Computer science)
615  0$aWind power$xForecasting.
615  0$aWind power plants$xForecasting.
615  0$aNeural networks (Computer science)
701   $aLiu$b Z$01405433
712 02$aNational Renewable Energy Laboratory (U.S.)
712 12$aIEEE Energy Conversion Congress and Exposition$f(2012 :$eRaleigh, N.C.)
801  0$bGPO
801  1$bGPO
906   $aBOOK
912   $a9910702192403321
996   $aWind power plant prediction by using neural networks$93481905
997   $aUNINA