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dc.contributor.authorPrada Moraga, César de 
dc.contributor.authorHose, Dominik
dc.contributor.authorGutierrez, Gloria
dc.contributor.authorPitarch Pérez, José Luis 
dc.date.accessioned2018-05-07T10:15:00Z
dc.date.available2018-05-07T10:15:00Z
dc.date.issued2018
dc.identifier.citationFelix Breitenecker, Wolfgang Kemmetmüller, Andreas Körner, Andreas Kugi and Inge Troch. 9th Vienna International Conference on Mathematical Modelling. Viena: TU Wien, 2018, p. 523-528es
dc.identifier.urihttp://uvadoc.uva.es/handle/10324/29487
dc.descriptionProducción Científicaes
dc.description.abstractThis paper presents a methodology for developing grey models of process systems, that is, models that, being based on fundamental principles and laws of nature, combine them with sub-models obtained from experimental data. The method follows two steps: the first one takes advantage of what is known, while the second uses the data and mixed-integer optimization algorithms to identify the structure and parameters of the remaining parts of the model. The method is illustrated in a challenging biotechnological process: the Acetone-Butanol-Ethanol (ABE) fermentation process.es
dc.format.extent6 p.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherElsevieres
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by-sa/4.0/
dc.subject.classificationmodelling methodologyes
dc.subject.classificationgrey-box modeles
dc.subject.classificationstructurees
dc.subject.classificationidentificationes
dc.subject.classificationfermentation processes
dc.titleDeveloping Grey-Box Dynamic Process Modelses
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.rights.holderElsevieres
dc.identifier.doi10.1016/j.ifacol.2018.03.088es
dc.relation.publisherversionhttps://doi.org/10.1016/j.ifacol.2018.03.088es
dc.title.event9th Vienna International Conference on Mathematical Modelling (MATHMOD 2018)es
dc.description.projectMINECO/FEDER Grant DPI2015-70975 (INOPTCON)es
dc.description.projectEU H2020-SPIRE Grant Agreement nº 723575 (CoPro)es
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/723575
dc.rightsAttribution-ShareAlike 4.0 International


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