Research on Sample Selection of Urban Rail Transit Passenger Flow Forecasting Based on SCBP Algorithm

Due to the wide applications of deep learning in the field of urban rail transit passenger flow forecasting, the selection problem of training samples has become increasingly more worthy of researchers' attention, as it is closely related to urban rail transit passenger flow time series. Theref...

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Veröffentlicht in:	IEEE access 2020, Vol.8, p.89425-89438
Hauptverfasser:	Lu, Wenbo, Ma, Chaoqun, Li, Peikun
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms artificial neural network Computer Science Computer Science, Information Systems Deep learning Engineering Engineering, Electrical & Electronic Flow characteristics Forecasting grey wolf optimizer algorithm Linear equations Machine learning Neural networks Optimization passenger flow forecast Passengers Prediction algorithms Rail transit Rails sample selection Science & Technology Technology Telecommunications Training Urban rail
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