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dc.contributor.advisorVirkler, Mark Roberteng
dc.contributor.authorAmado, Vanessa, 1973-eng
dc.coverage.spatialPuerto Rico -- San Juaneng
dc.date.issued2008eng
dc.date.submitted2008 Springeng
dc.descriptionThe entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.eng
dc.descriptionTitle from title screen of research.pdf file (viewed on June 8, 2009)eng
dc.descriptionVita.eng
dc.descriptionThesis (Ph. D.) University of Missouri-Columbia 2008.eng
dc.description.abstractArchived traffic-generated data (traffic flow, accident, work-zone, and weather data) from PR-18 in San Juan was examined by means of association mining and the KDD process. A total of six studies were developed and studied using the IBM Intelligent Miner for Data. The objective was to gain knowledge from the data about interrelationship between the variables. The approach was found to be a source of valuable information that allowed the identification of: red flags during work-zone operations; similar patterns in LOS between Tuesdays and Wednesdays and similar patterns in LOS between Mondays, Thursdays, and Fridays; and allowed the analysis of LOS over time. The approach also allowed the identification of temporary traffic control devices impacted by vehicles, common accidents, and day of the week with worst LOS. New regulations could arise from the information learned that could be used to improve work-zone operations for the safety of drivers and construction worker.eng
dc.description.bibrefIncludes bibliographical referenceseng
dc.identifier.merlinb68772853eng
dc.identifier.oclc373874180eng
dc.identifier.urihttps://hdl.handle.net/10355/5591
dc.identifier.urihttps://doi.org/10.32469/10355/5591eng
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcommunityUniversity of Missouri--Columbia. Graduate School. Theses and Dissertationseng
dc.rightsOpenAccess.eng
dc.rights.licenseThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.
dc.subject.lcshData miningeng
dc.subject.lcshTraffic floweng
dc.subject.lcshRoad work zoneseng
dc.titleKnowledge discovery and data mining from freeway section traffic dataeng
dc.typeThesiseng
thesis.degree.disciplineCivil engineering (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelDoctoraleng
thesis.degree.namePh. D.eng


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