A Hybrid Population Distribution Prediction Approach Integrating LSTM and CA Models with Micro-Spatiotemporal Granularity: A Case Study of Chongming District, Shanghai

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datacite.relatedItem.firstPage544
datacite.relatedItem.issue8
datacite.relatedItem.relatedIdentifierTypeISSN
datacite.relatedItem.relatedItemIdentifier2220-9964
datacite.relatedItem.relationTypeIsPublishedIn
datacite.relatedItem.titleIJGI
datacite.relatedItem.volume10
dc.contributor.authorPengyuan Wang
dc.contributor.authorXiao Huang
dc.contributor.authorJoseph Mango
dc.contributor.authorDi Zhang
dc.contributor.authorDong Xu
dc.contributor.authorXiang Li
dc.date.accessioned2025-05-14T12:53:40Z
dc.date.available2025-05-14T12:53:40Z
dc.date.issued2021
dc.identifier.doihttps://doi.org/10.3390/ijgi10080544
dc.identifier.otherjz000145-0540
dc.identifier.urihttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/21946
dc.publisherMDPI AG
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc550
dc.titleA Hybrid Population Distribution Prediction Approach Integrating LSTM and CA Models with Micro-Spatiotemporal Granularity: A Case Study of Chongming District, Shanghai
dc.typeArticle
dcat.distribution.pdfhttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/21947
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