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Parameter estimation of the kinetic α -pinene isomerization model using the MCSfilter algorithm

dc.contributor.authorAmador, Andreia
dc.contributor.authorFernandes, Florbela P.
dc.contributor.authorSantos, Lino O.
dc.contributor.authorRomanenko, Andrey
dc.contributor.authorRocha, Ana Maria A.C.
dc.date.accessioned2020-04-07T11:03:29Z
dc.date.available2020-04-07T11:03:29Z
dc.date.issued2018
dc.description.abstractThis paper aims to illustrate the application of a derivative- free multistart algorithm with coordinate search filter, designated as the MCSFilter algorithm. The problem used in this study is the parameter estimation problem of the kinetic α-pinene isomerization model. This is a well known nonlinear optimization problem (NLP) that has been investigated as a case study for performance testing of most derivative based methods proposed in the literature. Since the MCSFilter algorithm features a stochastic component, it was run ten times to solve the NLP problem. The optimization problem was successfully solved in all the runs and the optimal solution demonstrates that in all runs the MCSFilter provides a good quality solution.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAmador, Andreia: Fernandes, Florbela; Santos, Lino O.; Romanenko, Andrey; Rocha, Ana M.A.C. (2018). Parameter estimation of the kinetic α -pinene isomerization model using the MCSfilter algorithm. In 18th International Conference on Computational Science and Its Applications, ICCSA 2018; Melbourne. p. 624-636. ISBN 978-3-319-95165-2pt_PT
dc.identifier.doi10.1007/978-3-319-95165-2_44pt_PT
dc.identifier.issn978-3-319-95165-2
dc.identifier.urihttp://hdl.handle.net/10198/21581
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringer Verlagpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/pt_PT
dc.subjectMCSFilterpt_PT
dc.subjectα-pinene isomerization modelpt_PT
dc.subjectDerivativo free optimizationpt_PT
dc.titleParameter estimation of the kinetic α -pinene isomerization model using the MCSfilter algorithmpt_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferencePlaceMelbourne, Austráliapt_PT
oaire.citation.endPage636pt_PT
oaire.citation.startPage624pt_PT
oaire.citation.titleICCSA 2018pt_PT
oaire.citation.volume10961pt_PT
person.familyNameFernandes
person.givenNameFlorbela P.
person.identifier.ciencia-id501D-6FD0-CC53
person.identifier.orcid0000-0001-9542-4460
person.identifier.scopus-author-id35179471000
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication1f7a9fde-7a4d-4b2c-8f9d-dab571163c33
relation.isAuthorOfPublication.latestForDiscovery1f7a9fde-7a4d-4b2c-8f9d-dab571163c33

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