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Metro Passenger Flow Prediction Model Using Attention Based Neural Network
Metro passenger flow prediction plays an essential role in metro operation system. Due to characteristics of metro operation system, the station operation state is difficult to be described by the passenger flow at a single station. Thus, a novel attention mechanism based end-to-end neural network is presented to predict the inbound and outbound passenger flow to improve predictive effect. The novel model explores the latent dependency between flow of forecast target station and historicaldoi:10.1109/access.2020.2973406 fatcat:ozbr33cv2vbtnirvta77njvgom