LEADER 01683nam  2200433   450 
001 9910424647303321
005 20230830164628.0
010   $a1-83968-084-9
035   $a(CKB)4100000011568899
035   $a(NjHacI)994100000011568899
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/67730
035   $a(EXLCZ)994100000011568899
100   $a20221022d2020      uy             0
101 0 $aeng
135   $aur|||||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aDynamic Data Assimilation $eBeating the Uncertainties /$fedited by Dinesh G. Harkut
210   $cIntechOpen$d2020
210  1$aLondon :$cIntechOpen,$d2020.
215   $a1 online resource (118 pages) $cillustrations
311   $a1-83968-083-0 
320   $aIncludes bibliographical references.
330   $aData assimilation is a process of fusing data with a model for the singular purpose of estimating unknown variables. It can be used, for example, to predict the evolution of the atmosphere at a given point and time. This book examines data assimilation methods including Kalman filtering, artificial intelligence, neural networks, machine learning, and cognitive computing.
517   $aDynamic data assimilation
606   $aMathematical models
606   $aSimulation methods
610   $aApplied mathematics
615  0$aMathematical models.
615  0$aSimulation methods.
676   $a511.8
702   $aHarkut$b Dinesh G.$f1988-
801  0$bNjHacI
801  1$bNjHacl
906   $aBOOK
912   $a9910424647303321
996   $aDynamic Data Assimilation$92952332
997   $aUNINA