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A panel data analysis of the electric mobility deployment in the Eropean Union

dc.contributor.authorGruetzmacher, Sarah
dc.contributor.authorVaz, Clara B.
dc.contributor.authorFerreira, Ângela P.
dc.date.accessioned2023-03-01T15:34:01Z
dc.date.available2023-03-01T15:34:01Z
dc.date.issued2021
dc.description.abstractThis study aims to find and develop an appropriate optimization approach to reduce the time and labor employed throughout a given chemical process and could be decisive for quality management. In this context, this work presents a comparative study of two optimization approaches using real experimental data from the chemical engineering area, reported in a previous study [4].The first approach is based on the traditional response surface method and the second approach combines the response surface method with genetic algorithm and data mining. The main objective is to optimize the surface function based on three variables using hybrid genetic algorithms combined with cluster analysis to reduce the number of experiments and to find the closest value to the optimum within the established restrictions. The proposed strategy has proven to be promising since the optimal value was achieved without going through derivability unlike conventional methods, and fewer experiments were required to find the optimal solution in comparison to the previous work using the traditional response surface method.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationGruetzmacher, Sarah; Vaz, Clara B.; Ferreira, Ângela P. (2021). A panel data analysis of the electric mobility deployment in the Eropean Union. In International Conference on Optimization Learning Algorithms and Applications. Bragançapt_PT
dc.identifier.urihttp://hdl.handle.net/10198/27384
dc.language.isoengpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.titleA panel data analysis of the electric mobility deployment in the Eropean Unionpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceBragançapt_PT
oaire.citation.titleInternational Conference on Optimization Learning Algorithms and Applicationspt_PT
person.familyNameGruetzmacher
person.familyNameVaz
person.familyNameFerreira
person.givenNameSarah
person.givenNameClara B.
person.givenNameÂngela P.
person.identifierR-001-FQC
person.identifier.ciencia-id9611-3386-E516
person.identifier.ciencia-id2211-6787-D936
person.identifier.orcid0000-0002-1193-4461
person.identifier.orcid0000-0001-9862-6068
person.identifier.orcid0000-0002-1912-2556
person.identifier.ridF-1519-2016
person.identifier.ridM-8188-2013
person.identifier.scopus-author-id57216177941
person.identifier.scopus-author-id56352045500
person.identifier.scopus-author-id55516840300
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication38bea487-fafc-4719-be03-783c8b9dae6c
relation.isAuthorOfPublication34bc350c-28d9-4b06-9874-b2b0dba58d1d
relation.isAuthorOfPublication3fec941d-79fb-4901-918d-a34ffa0195cc
relation.isAuthorOfPublication.latestForDiscovery34bc350c-28d9-4b06-9874-b2b0dba58d1d

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