Predicting Station-Level Short-Term Passenger Flow in a Citywide Metro Network Using Spatiotemporal Graph Convolutional Neural Networks

dc.contributor.authorYong Han
dc.contributor.authorShukang Wang
dc.contributor.authorYibin Ren
dc.contributor.authorCheng Wang
dc.contributor.authorPeng Gao
dc.contributor.authorGe Chen
dc.date.accessioned2025-05-14T15:17:47Z
dc.date.available2025-05-14T15:17:47Z
dc.identifier.urihttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/28253
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc550
dc.titlePredicting Station-Level Short-Term Passenger Flow in a Citywide Metro Network Using Spatiotemporal Graph Convolutional Neural Networks
dc.typepdf
dspace.entity.typeDistribution
relation.isDatasetOfDistributionf677b659-aaf3-41c0-817e-c7f7f538cbe3
relation.isDatasetOfDistribution.latestForDiscoveryf677b659-aaf3-41c0-817e-c7f7f538cbe3

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
ijgi-08-06-00243.pdf
Size:
10.19 MB
Format:
Adobe Portable Document Format

Collections