LSTM-Based Transformer for Transfer Passenger Flow Forecasting between Transportation Integrated Hubs in Urban Agglomeration

A crucial component of multimodal transportation networks and long-distance travel chains is the forecasting of transfer passenger flow between integrated hubs in urban agglomerations, particularly during periods of high passenger flow or unusual weather. Deep learning is better suited to managing m...

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Hlavní autoři:	Min Yue, Shuhong Ma
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2023-01-01
Edice:	Applied Sciences
Témata:	transfer passenger flow forecasting transformer deep learning long short-term memory multimodal transportation system
On-line přístup:	https://www.mdpi.com/2076-3417/13/1/637
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