Empirical mode decomposition based long short-term memory neural network forecasting model for the short-term metro passenger flow

Short-term metro passenger flow forecasting is an essential component of intelligent transportation systems (ITS) and can be applied to optimize the passenger flow organization of a station and offer data support for metro passenger flow early warning and system management. LSTM neural networks have...

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Detalles Bibliográficos
Autores principales: Chen, Quanchao, Wen, Di, Li, Xuqiang, Chen, Dingjun, Lv, Hongxia, Zhang, Jie, Gao, Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6738919/
https://www.ncbi.nlm.nih.gov/pubmed/31509599
http://dx.doi.org/10.1371/journal.pone.0222365

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6738919/
https://www.ncbi.nlm.nih.gov/pubmed/31509599
http://dx.doi.org/10.1371/journal.pone.0222365

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