Prediction of Passenger Flow in Urban Rail Transit Based on Big Data Analysis and Deep Learning

Prediction of Passenger Flow in Urban Rail Transit Based on Big Data Analysis and Deep Learning

Passenger flow prediction is the key to operation efficiency and safety of urban rail transit (URT). This paper combines the deep learning (DL) theory and support vector machine (SVM) into the DL-SVM model for URT passenger flow prediction. Firstly, the deep belief network (DBN) was adopted to extra...

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Bibliographic Details
Main Authors: Kaer Zhu, Ping Xun, Wei Li, Zhen Li, Ruochong Zhou
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Big data analysis
deep belief network (DBN)
support vector machine (SVM)
passenger flow prediction
urban rail transit (URT)
Online Access:https://ieeexplore.ieee.org/document/8853313/

Internet

https://ieeexplore.ieee.org/document/8853313/

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