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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Marcelino, P. | pt_BR |
dc.contributor.author | Antunes, M. L. | pt_BR |
dc.contributor.author | Fortunato, E. | pt_BR |
dc.date.accessioned | 2019-11-18T11:06:53Z | pt_BR |
dc.date.accessioned | 2019-12-05T10:28:17Z | - |
dc.date.available | 2019-11-18T11:06:53Z | pt_BR |
dc.date.available | 2019-12-05T10:28:17Z | - |
dc.date.issued | 2017-04-20 | pt_BR |
dc.identifier.uri | https://repositorio.lnec.pt/jspui/handle/123456789/1012109 | - |
dc.description.abstract | This 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.iso | por | pt_BR |
dc.publisher | FEUP | pt_BR |
dc.rights | restrictedAccess | pt_BR |
dc.subject | Data analysis | pt_BR |
dc.subject | Data science | pt_BR |
dc.subject | Data visualization | pt_BR |
dc.subject | Pavement engineering | pt_BR |
dc.subject | Python | pt_BR |
dc.title | Exploratory Data Analysis in Pavement Engineering Using Python | pt_BR |
dc.type | workingPaper | pt_BR |
dc.identifier.local | Porto | pt_BR |
dc.description.sector | DT/NIT | pt_BR |
dc.identifier.conftitle | XXIV Jornadas de Classificação e Análise de Dados (JOCLAD2017) | pt_BR |
dc.contributor.peer-reviewed | SIM | pt_BR |
dc.contributor.academicresearchers | SIM | pt_BR |
dc.contributor.arquivo | NAO | pt_BR |
Appears in Collections: | DT/NIT - Comunicações a congressos e artigos de revista |
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