Short-Term Passenger Flow Prediction of Urban Rail Transit Based on a Combined Deep Learning Model

It is difficult for a single model to simultaneously capture the nonlinear, correlation, and periodicity of data series in the passenger flow prediction of urban rail transit (URT). To better predict the short-term passenger flow of URT, based on the long short-term memory network (LSTM) model, a de...

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Hlavní autoři:	Zhongwei Hou, Zixue Du, Guang Yang, Zhen Yang
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2022-07-01
Edice:	Applied Sciences
Témata:	short-term passenger flow of urban rail transit passenger flow prediction deep learning long short-term memory network temporal convolutional network
On-line přístup:	https://www.mdpi.com/2076-3417/12/15/7597
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