Construction Demand Forecasting Based on Conventional and Supervised Machine Learning Methods

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 Construction demand forecasting based on conventional and supervised machine learning methods (Unpublished thesis).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

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