Efficient Characterization of Uncertain Model Parameters with a Reduced-Order Ensemble Kalman Filter

Efficient Characterization of Uncertain Model Parameters with a Reduced-Order Ensemble Kalman Filter

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Spatially variable model parameters are often highly uncertain and difficult to observe. This has prompted the widespread use of Bayesian characterization methods that can infer parameter values from measurements of related variables, while explicitly accounting for uncertainty. Ensemble versions of...

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Bibliographic Details
Main Authors: Lin, Binghuai, McLaughlin, Dennis
Other Authors: Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Format: Article
Language:en_US
Published: Society for Industrial and Applied Mathematics 2014
Online Access:http://hdl.handle.net/1721.1/88205

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