Using Data Mining Techniques to Predict Groundwater Levels: A Case Study of the Edwards Aquifer

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dc.contributor.advisorSchwartz, Benjamin F.
dc.contributor.advisorYuan, Yihong
dc.contributor.authorDedeaux, Lenee A.
dc.contributor.committeeMemberGreen, Ronald T.
dc.date.accessioned2018-09-19T20:48:17Z
dc.date.available2018-09-19T20:48:17Z
dc.date.issued2017-04
dc.description.abstractNo abstract prepared.
dc.description.departmentBiology
dc.formatText
dc.format.extent110 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationDedeaux, L. A. (2017). <i>Using data mining techniques to predict groundwater levels: A case study of the Edwards Aquifer</i> (Unpublished thesis). Texas State University, San Marcos, Texas.
dc.identifier.urihttps://hdl.handle.net/10877/7735
dc.language.isoen
dc.subjectData mining
dc.subjectArtificial neural network
dc.subjectClustering
dc.subjectMissing data
dc.subjectData gaps
dc.subjectANN
dc.titleUsing Data Mining Techniques to Predict Groundwater Levels: A Case Study of the Edwards Aquifer
dc.typeThesis
thesis.degree.departmentBiology
thesis.degree.disciplineAquatic Resources
thesis.degree.grantorTexas State University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science

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