A Novel Approach Based on Machine Learning and Public Engagement to Predict Water-Scarcity Risk in Urban Areas

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datacite.relatedItem.firstPage606
datacite.relatedItem.issue12
datacite.relatedItem.relatedIdentifierTypeISSN
datacite.relatedItem.relatedItemIdentifier2220-9964
datacite.relatedItem.relationTypeIsPublishedIn
datacite.relatedItem.titleIJGI
datacite.relatedItem.volume11
dc.contributor.authorSadeq Khaleefah Hanoon
dc.contributor.authorAhmad Fikri Abdullah
dc.contributor.authorHelmi Z. M. Shafri
dc.contributor.authorAimrun Wayayok
dc.date.accessioned2025-05-14T14:18:16Z
dc.date.available2025-05-14T14:18:16Z
dc.date.issued2022
dc.identifier.doihttps://doi.org/10.3390/ijgi11120606
dc.identifier.otherjz000147-0600
dc.identifier.urihttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/25588
dc.publisherMDPI AG
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc550
dc.titleA Novel Approach Based on Machine Learning and Public Engagement to Predict Water-Scarcity Risk in Urban Areas
dc.typeArticle
dcat.distribution.pdfhttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/25589
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