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1 Ergebnisse
1
Spatio-temporal similarity between stations:
Di Yang
;
Ruixue Wu
;
Peng Wang
.
doi:10.1371/journal.pone.0298684.g007. , 2024
Link:
https://doi.org/10.1371/journal.pone.0298684.g007
RT Journal T1
Spatio-temporal similarity between stations
UL https://suche.suub.uni-bremen.de/peid=base-ftgriffithunifig:oai:figshare.com:article_25361849&Exemplar=1&LAN=DE A1 Di Yang A1 Ruixue Wu A1 Peng Wang A1 Yanfang Li YR 2024 K1 Medicine K1 Neuroscience K1 Biotechnology K1 Science Policy K1 Infectious Diseases K1 Biological Sciences not elsewhere classified K1 Mathematical Sciences not elsewhere classified K1 Information Systems not elsewhere classified K1 usage pattern similarity K1 bring great challenges K1 station flow features K1 citi bike dataset K1 bike allocation rebalancing K1 dual network structure K1 sharing demand prediction K1 sharing demand K1 station planning K1 final prediction K1 based dual K1 sharing systems K1 bike borrowing K1 user behavior K1 temporal characteristics K1 temporal accuracy K1 scale spatio K1 fully considered K1 bikes unbalanced K1 address limitations JF doi:10.1371/journal.pone.0298684.g007 LK http://dx.doi.org/https://doi.org/10.1371/journal.pone.0298684.g007 DO https://doi.org/10.1371/journal.pone.0298684.g007 SF ELIB - SuUB Bremen
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