Examining thermokarst initiation with random forest models
Master's Project (M.S.) University of Alaska Fairbanks, 2020 This project examines thermokarst initiation through the application of random forest models. Thermokarst initiation marks the start of the formation of thermokarst features. Changes in landscape, due to the thermokarst process, can r...
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ftunivalaska:oai:scholarworks.alaska.edu:11122/11879 2023-05-15T18:32:53+02:00 Examining thermokarst initiation with random forest models Spicer, Rawser W. Bolton, W. Robert Lawlor, Orion Chappell, Glenn 2020-05 http://hdl.handle.net/11122/11879 en_US eng http://hdl.handle.net/11122/11879 Department of Computer Science Master's Project ms 2020 ftunivalaska 2023-02-23T21:37:47Z Master's Project (M.S.) University of Alaska Fairbanks, 2020 This project examines thermokarst initiation through the application of random forest models. Thermokarst initiation marks the start of the formation of thermokarst features. Changes in landscape, due to the thermokarst process, can result in changes in wildlife habitat, as well as energy, carbon and water fluxes. Random forests are an ensemble learning technique that combines the results of many independent decision trees to create results that avoid the overfitting in regular decision trees. Random forests were trained against an existing thermokarst initiation model. Results showed that random forests were useful in this context. Random forest hyperparameters were also examined through a multiparameter sensitivity analysis. Other/Unknown Material Thermokarst Alaska University of Alaska: ScholarWorks@UA Fairbanks |
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Open Polar |
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University of Alaska: ScholarWorks@UA |
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ftunivalaska |
language |
English |
description |
Master's Project (M.S.) University of Alaska Fairbanks, 2020 This project examines thermokarst initiation through the application of random forest models. Thermokarst initiation marks the start of the formation of thermokarst features. Changes in landscape, due to the thermokarst process, can result in changes in wildlife habitat, as well as energy, carbon and water fluxes. Random forests are an ensemble learning technique that combines the results of many independent decision trees to create results that avoid the overfitting in regular decision trees. Random forests were trained against an existing thermokarst initiation model. Results showed that random forests were useful in this context. Random forest hyperparameters were also examined through a multiparameter sensitivity analysis. |
author2 |
Bolton, W. Robert Lawlor, Orion Chappell, Glenn |
format |
Other/Unknown Material |
author |
Spicer, Rawser W. |
spellingShingle |
Spicer, Rawser W. Examining thermokarst initiation with random forest models |
author_facet |
Spicer, Rawser W. |
author_sort |
Spicer, Rawser W. |
title |
Examining thermokarst initiation with random forest models |
title_short |
Examining thermokarst initiation with random forest models |
title_full |
Examining thermokarst initiation with random forest models |
title_fullStr |
Examining thermokarst initiation with random forest models |
title_full_unstemmed |
Examining thermokarst initiation with random forest models |
title_sort |
examining thermokarst initiation with random forest models |
publishDate |
2020 |
url |
http://hdl.handle.net/11122/11879 |
geographic |
Fairbanks |
geographic_facet |
Fairbanks |
genre |
Thermokarst Alaska |
genre_facet |
Thermokarst Alaska |
op_relation |
http://hdl.handle.net/11122/11879 Department of Computer Science |
_version_ |
1766217085314138112 |