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1 Ergebnisse
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A dynamic graph deep learning model with multivariate empir..:
Huang, Hao
;
Mao, Jiannan
;
Kang, Leilei
...
Computer-Aided Civil and Infrastructure Engineering. 39 (2024) 17 - p. 2596-2618 , 2024
Link:
https://doi.org/10.1111/mice.13214
RT Journal T1 <Title>A dynamic graph deep learning model with multivariate empirical mode decomposition for network‐wide metro passenger flow prediction</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1111_mice.13214&Exemplar=1&LAN=DE A1 Huang, Hao A1 Mao, Jiannan A1 Kang, Leilei A1 Lu, Weike A1 Zhang, Sijia A1 Liu, Lan PB Wiley YR 2024 SN 1093-9687 SN 1467-8667 JF Computer-Aided Civil and Infrastructure Engineering VO 39 IS 17 SP 2596 OP 2618 LK http://dx.doi.org/https://doi.org/10.1111/mice.13214 DO https://doi.org/10.1111/mice.13214 SF ELIB - SuUB Bremen
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