Metro passenger flow prediction: a double-stage decomposition combined with Enhanced-BiGRU model considering multiple factors
Author:
Affiliation:
1. Changchun University of Science and Technology, China
2. Nankai University, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3652628.3652787
Reference13 articles.
1. Wang X. Shi R. & Zhou Y. 2020. Dynamics of urban sprawl and sustainable development in China. Socio-Economic Planning Sciences 70 100736. Doi: https://doi.org/10.1016/j.seps.2019.100736
2. Zhong C Batty M Manley E 2016. Variability in regularity: Mining temporal mobility patterns in London Singapore and Beijing using smart-card data[J]. PloS one 11(2): e0149222.doi: https://doi.org/10.1371/journal.pone.0149222
3. Public transport for smart cities: Recent innovations and future challenges
4. Smart cities, big data and urban policy: Towards urban analytics for the long run
5. DEASeq2Seq: An attention based sequence to sequence model for short-term metro passenger flow prediction within decomposition-ensemble strategy
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