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Impacts on glacier mass balance in High Mountain Asia assessed using machine learning

dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorKraaijenbrink, Philip
dc.contributor.authorHartmann, David
dc.date.accessioned2022-09-09T02:00:45Z
dc.date.available2022-09-09T02:00:45Z
dc.date.issued2022
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/42505
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectIn this study, the glacier melt of 8099 glaciers in High Mountain Asia was modelled with machine learning based on 6 climatic and 10 morphological variables. These models are multiple linear regression, Random Forest, XGBoost and artificial neural network. With the models, the effects of each variable on the glacier mass balance was assessed.
dc.titleImpacts on glacier mass balance in High Mountain Asia assessed using machine learning
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.courseuuApplied Data Science
dc.thesis.id9161


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