Please use this identifier to cite or link to this item: http://repositorio.lnec.pt:8080/jspui/handle/123456789/1002606
Title: Bayesian Estimation in Dam Monitoring Networks
Authors: Casaca, J. M.
Mateus, P. B.
Coelho, J. I.
Keywords: Bayes estimator;Hyper-parameter;Parametric elicitation
Issue Date: 1-Feb-2011
Publisher: David Publishing Company
Abstract: Summary: A Bayesian estimator with informative prior distributions (a multi-normal and an inverted gamma distribution), adequate to displacement estimation at dam monitoring net-works, is presented. The hyper-parameters of the prior distributions are obtained by Bayesian empirical methods with non-informative priors. The performances of the Bayes estimator and the classical generalized lest squares estimator are compared using two measurements of the horizontal monitoring network of a concrete gravity dam: the Penha Garcia dam (Portugal). In order to test the robustness of the two estimators, gross errors are added to one of the measured horizontal directions: the Bayes estimator proves to be significantly more robust than the generalized least squares estimator.
URI: http://repositorio.lnec.pt:8080/jspui/handle/123456789/1002606
Appears in Collections:DBB/NGA - Comunicações a congressos e artigos de revista

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