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dc.contributor.advisorAmeri, Farhad
dc.contributor.authorGhanbari, Ali ( )
dc.date.accessioned2019-05-07T20:36:07Z
dc.date.available2019-05-07T20:36:07Z
dc.date.issued2019-05
dc.identifier.citationGhanbari, A. (2019). Construction demand forecasting based on conventional and supervised machine learning methods (Unpublished thesis). Texas State University, San Marcos, Texas.
dc.identifier.urihttps://digital.library.txstate.edu/handle/10877/8164
dc.description.abstractNo abstract prepared.
dc.formatText
dc.format.extent140 pages
dc.format.medium1 file (.pdf)
dc.language.isoen
dc.subjectConstruction
dc.subjectDemand
dc.subjectIndicator
dc.subjectMachine learning
dc.subjectTotal market size
dc.subjectTotal fleet size
dc.subject.lcshBusiness logistics
dc.subject.lcshSupply and demand--Forecasting
dc.subject.lcshMachine learning
dc.titleConstruction Demand Forecasting Based on Conventional and Supervised Machine Learning Methods
txstate.documenttypeThesis
dc.contributor.committeeMemberMendez Mediavilla, Francis A.
dc.contributor.committeeMemberTorres, Anthony
thesis.degree.departmentEngineering Technology
thesis.degree.disciplineTechnology Management
thesis.degree.grantorTexas State University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science
txstate.departmentEngineering Technology


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