House Price Valuation Model Based on Geographically Neural Network Weighted Regression: The Case Study of Shenzhen, China

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datacite.relatedItem.firstPage450
datacite.relatedItem.issue8
datacite.relatedItem.relatedIdentifierTypeISSN
datacite.relatedItem.relatedItemIdentifier2220-9964
datacite.relatedItem.relationTypeIsPublishedIn
datacite.relatedItem.titleIJGI
datacite.relatedItem.volume11
dc.contributor.authorZimo Wang
dc.contributor.authorYicheng Wang
dc.contributor.authorSensen Wu
dc.contributor.authorZhenhong Du
dc.date.accessioned2025-05-14T14:04:26Z
dc.date.available2025-05-14T14:04:26Z
dc.date.issued2022
dc.identifier.doihttps://doi.org/10.3390/ijgi11080450
dc.identifier.otherjz000147-0444
dc.identifier.urihttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/24964
dc.publisherMDPI AG
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc550
dc.titleHouse Price Valuation Model Based on Geographically Neural Network Weighted Regression: The Case Study of Shenzhen, China
dc.typeArticle
dcat.distribution.pdfhttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/24965
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