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dc.contributor.authorJuznic Zonta, Zivko
dc.contributor.authorFlotats Ripoll, Xavier
dc.contributor.authorMagrí Aloy, Albert
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Agroalimentària i Biotecnologia
dc.date.accessioned2014-12-10T11:47:05Z
dc.date.created2014-07-03
dc.date.issued2014-07-03
dc.identifier.citationJuznic, Z.; Flotats, X.; Magrí, A. Estimation of parameter uncertainty for an activated sludge model using Bayesian inference: a comparison with the frequentist method. "Environmental technology", 03 Juliol 2014, vol. 35, núm. 13, p. 1618-1629.
dc.identifier.issn0959-3330
dc.identifier.urihttp://hdl.handle.net/2117/24979
dc.description.abstractThe procedure commonly used for the assessment of the parameters included in activated sludge models (ASMs) relies on the estimation of their optimal value within a confidence region (i.e. frequentist inference). Once optimal values are estimated, parameter uncertainty is computed through the covariance matrix. However, alternative approaches based on the consideration of the model parameters as probability distributions (i.e. Bayesian inference), may be of interest. The aim of this work is to apply (and compare) both Bayesian and frequentist inference methods when assessing uncertainty for an ASM-type model, which considers intracellular storage and biomass growth, simultaneously. Practical identifiability was addressed exclusively considering respirometric profiles based on the oxygen uptake rate and with the aid of probabilistic global sensitivity analysis. Parameter uncertainty was thus estimated according to both the Bayesian and frequentist inferential procedures. Results were compared in order to evidence the strengths and weaknesses of both approaches. Since it was demonstrated that Bayesian inference could be reduced to a frequentist approach under particular hypotheses, the former can be considered as a more generalist methodology. Hence, the use of Bayesian inference is encouraged for tackling inferential issues in ASM environments.
dc.format.extent12 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències
dc.subject.lcshSewage sludge--Analysis
dc.subject.otherMarkov chain Monte Carlo
dc.subject.otherparameter uncertainty
dc.subject.otherHessian
dc.subject.otheractivated sludge model
dc.subject.otherBayesian
dc.subject.otherSENSITIVITY-ANALYSIS
dc.subject.otherAEROBIC CONDITIONS
dc.subject.otherPRACTICAL IDENTIFIABILITY
dc.subject.otherGROWTH-PROCESSES
dc.subject.otherSYSTEMS
dc.subject.otherSTORAGE
dc.subject.otherWASTEWATERS
dc.subject.otherCULTURES
dc.subject.otherDESIGN
dc.titleEstimation of parameter uncertainty for an activated sludge model using Bayesian inference: a comparison with the frequentist method
dc.typeArticle
dc.subject.lemacBiomatemàtica
dc.contributor.groupUniversitat Politècnica de Catalunya. GREA - Grup de Recerca d'Enginyeria Agro-Ambiental
dc.identifier.doi10.1080/09593330.2013.876450
dc.relation.publisherversionhttp://www.tandfonline.com/doi/abs/10.1080/09593330.2013.876450#.U19tFFV_uSo
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac14159762
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
local.citation.authorJuznic, Z.; Flotats, X.; Magrí, A.
local.citation.publicationNameEnvironmental technology
local.citation.volume35
local.citation.number13
local.citation.startingPage1618
local.citation.endingPage1629


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