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Advanced utilization of multi-learning algorithm: ensemble super learner to map groundwater potential for potable mineral water
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Sanghoon | - |
dc.contributor.author | Kaown, Dugin | - |
dc.contributor.author | Koh, Eun-Hee | - |
dc.contributor.author | Lee, Hye-Lim | - |
dc.contributor.author | Ko, Kyung-Seok | - |
dc.contributor.author | Lee, Kang-Kun | - |
dc.date.accessioned | 2022-06-24T08:29:08Z | - |
dc.date.available | 2022-06-24T08:29:08Z | - |
dc.date.created | 2022-05-19 | - |
dc.date.issued | 2022-01 | - |
dc.identifier.citation | Geocarto International | - |
dc.identifier.issn | 1010-6049 | - |
dc.identifier.uri | https://hdl.handle.net/10371/184107 | - |
dc.description.abstract | © 2022 Informa UK Limited, trading as Taylor & Francis Group.Although mapping the groundwater quality is crucial for people who require groundwater with strict quality standards, the ability to take intensive measurements has been restricted by a lack of groundwater accessibility. Thus, this study aimed to estimate and map the suitability of groundwater quality for use as potable mineral water. We attempted a novel approach by targeting comprehensive qualities for a specific groundwater use and by adopting a super learner that combines multiple different learning algorithms. The super learner generated a groundwater potential map indicating a zone with a high potential for mineral water and it outperformed the base learners by 21%–74%. Estimation results designated appropriate groundwater development locations for mineral water use, and assessment of predictors determined favorable environments. Consequently, the proposed approach presented a possible method for finding groundwater with the required quality for its optimal usage. Furthermore, it provided the possibility of worldwide application. | - |
dc.language | 영어 | - |
dc.publisher | Geocarto International Centre | - |
dc.title | Advanced utilization of multi-learning algorithm: ensemble super learner to map groundwater potential for potable mineral water | - |
dc.type | Article | - |
dc.identifier.doi | 10.1080/10106049.2022.2025921 | - |
dc.citation.journaltitle | Geocarto International | - |
dc.identifier.wosid | 000740912300001 | - |
dc.identifier.scopusid | 2-s2.0-85122760538 | - |
dc.description.isOpenAccess | N | - |
dc.contributor.affiliatedAuthor | Lee, Kang-Kun | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
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