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- Title
A Hybrid Temporal-Spatio Forecasting Approach for Passenger Flow Status in Chinese High-Speed Railway Transport Hub.
- Authors
Zhengyu Xie; Limin Jia; Yong Qin; LiWang
- Abstract
With the rapid development of high-speed railway in China, high-speed railway transport hub (HRTH) has become the high density distribution center of passenger flow. In order to accurately detect potential safety hazard hidden in passenger flow, it is necessary to forecast the status of passenger flow. In this paper,we proposed a hybrid temporal-spatio forecasting approach to obtain the passenger flow status in HRTH. The approach combined temporal forecasting based on radial basis function neural network (RBF NN) and spatio forecasting based on spatial correlation degree. Computational experiments on actual passenger flow status from a specific bottleneck position and its correlation points in HRTH showed that the proposed approach is effective to forecast the passenger flow status with high precision.
- Subjects
CHINA; RAILROADS; TRAFFIC flow; PASSENGERS; ARTIFICIAL neural networks; DISTRIBUTION (Probability theory); RADIAL basis functions
- Publication
Discrete Dynamics in Nature & Society, 2013, p1
- ISSN
1026-0226
- Publication type
Article
- DOI
10.1155/2013/239039