scholarly journals Fuzzy Temporal Logic Based Railway Passenger Flow Forecast Model

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Fei Dou ◽  
Limin Jia ◽  
Li Wang ◽  
Jie Xu ◽  
Yakun Huang
Keyword(s):  
Temporal Logic ◽  
High Speed ◽  
Nearest Neighbor ◽  
Forecast Accuracy ◽  
Forecast Model ◽  
Railway Transportation ◽  
Real World Data ◽  
High Speed Railway ◽  
Passenger Flow ◽  
Flow Forecast

Passenger flow forecast is of essential importance to the organization of railway transportation and is one of the most important basics for the decision-making on transportation pattern and train operation planning. Passenger flow of high-speed railway features the quasi-periodic variations in a short time and complex nonlinear fluctuation because of existence of many influencing factors. In this study, a fuzzy temporal logic based passenger flow forecast model (FTLPFFM) is presented based on fuzzy logic relationship recognition techniques that predicts the short-term passenger flow for high-speed railway, and the forecast accuracy is also significantly improved. An applied case that uses the real-world data illustrates the precision and accuracy of FTLPFFM. For this applied case, the proposed model performs better than thek-nearest neighbor (KNN) and autoregressive integrated moving average (ARIMA) models.

scholarly journals A Hybrid Temporal-Spatio Forecasting Approach for Passenger Flow Status in Chinese High-Speed Railway Transport Hub

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Zhengyu Xie ◽  
Limin Jia ◽  
Yong Qin ◽  
Li Wang
Keyword(s):  
High Speed ◽  
Rapid Development ◽  
Distribution Center ◽  
Railway Transport ◽  
High Speed Railway ◽  
Safety Hazard ◽  
Passenger Flow ◽  
Potential Safety ◽  
Correlation Degree ◽  
The Status

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.

scholarly journals Monitoring and Modeling Railway Structures on High-Speed Lines with Asphalt Concrete Underlay: A Study on the Bretagne–Pays de la Loire Line

2020 ◽  
Vol 2674 (12) ◽  
pp. 600-607
Author(s):  
Diana Khairallah ◽  
Olivier Chupin ◽  
Juliette Blanc ◽  
Pierre Hornych ◽  
Jean-Michel Piau ◽  
...  
Keyword(s):  
Asphalt Concrete ◽  
High Speed ◽  
Large Scale ◽  
Strain Gages ◽  
Railway Transportation ◽  
Dynamic Stresses ◽  
High Speed Railway ◽  
High Frequencies ◽  
High Acceleration ◽  
High Speed Trains

The design and durability of high-speed railway lines is a major challenge in the field of railway transportation. In France, 40 years of feedback on the field behavior of ballasted tracks led to improvements in the design rules. However, the settlement and wear of ballast, caused by dynamic stresses at high frequencies, remains a major problem on high-speed tracks leading to high maintenance costs. Studies have shown that this settlement is linked to the high acceleration produced in the ballast layer by high-speed trains traveling on the track, disrupting the granular assembly. The “Bretagne–Pays de la Loire” high-speed line (BPL HSL), with its varied subgrade conditions, represents the first large-scale application of asphalt concrete (GB) as the ballast sublayer. This line includes 77 km of conventional track with a granular sublayer of unbound granular material (UGM) and 105 km of track with an asphalt concrete sublayer under the ballast. During construction, instruments such as accelerometers, anchored deflection sensors, and strain gages, among others, were installed on four sections of the track. This paper examines the instrumentation as well as the acquisition system installed on the track. The data processing is explained first, followed by a presentation of the ViscoRail software, developed for modeling railway tracks. The bituminous section’s behavior and response is modeled using a multilayer dynamic response model, implemented in the ViscoRail software. A good match between experimental and calculated results is highlighted.

Sign in / Sign up

Export Citation Format

Share Document