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dc.contributor.editorHarkut, Dinesh G.
dc.date.accessioned2021-04-20T16:23:56Z
dc.date.available2021-04-20T16:23:56Z
dc.date.issued2020
dc.identifierONIX_20210420_9781839680847_3090
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/67730
dc.description.abstractData 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.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematicsen_US
dc.subject.otherApplied mathematics
dc.titleDynamic Data Assimilation
dc.title.alternativeBeating the Uncertainties
dc.typebook
oapen.identifier.doi10.5772/intechopen.87789
oapen.relation.isPublishedBy78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6
oapen.relation.isbn9781839680847
oapen.relation.isbn9781839680830
oapen.relation.isbn9781839680854
oapen.imprintIntechOpen
oapen.pages118


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