Please use this identifier to cite or link to this item: http://repositorio.lnec.pt:8080/jspui/handle/123456789/1012109
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dc.contributor.authorMarcelino, P.pt_BR
dc.contributor.authorAntunes, M. L.pt_BR
dc.contributor.authorFortunato, E.pt_BR
dc.date.accessioned2019-11-18T11:06:53Zpt_BR
dc.date.accessioned2019-12-05T10:28:17Z-
dc.date.available2019-11-18T11:06:53Zpt_BR
dc.date.available2019-12-05T10:28:17Z-
dc.date.issued2017-04-20pt_BR
dc.identifier.urihttps://repositorio.lnec.pt/jspui/handle/123456789/1012109-
dc.description.abstractThis paper presents an exploratory data analysis in pavement engineering problems using Python. A case study with data from the U.S. Long-Term Pavement Performance (LTPP) database illustrates Python applications for data analysis and visualization. This work demonstrated that Python can play an important role in the analysis of pavement engineering data, such as inventory, climate, traffic and pavement monitoring data. Further extensions of this research can lead to the development of more complex analyses, like the development of prediction models for pavement deterioration.pt_BR
dc.language.isoporpt_BR
dc.publisherFEUPpt_BR
dc.rightsrestrictedAccesspt_BR
dc.subjectData analysispt_BR
dc.subjectData sciencept_BR
dc.subjectData visualizationpt_BR
dc.subjectPavement engineeringpt_BR
dc.subjectPythonpt_BR
dc.titleExploratory Data Analysis in Pavement Engineering Using Pythonpt_BR
dc.typeworkingPaperpt_BR
dc.identifier.localPortopt_BR
dc.description.sectorDT/NITpt_BR
dc.identifier.conftitleXXIV Jornadas de Classificação e Análise de Dados (JOCLAD2017)pt_BR
dc.contributor.peer-reviewedSIMpt_BR
dc.contributor.academicresearchersSIMpt_BR
dc.contributor.arquivoNAOpt_BR
Appears in Collections:DT/NIT - Comunicações a congressos e artigos de revista

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