scholarly journals Prediction and Analysis of Train Passenger Load Factor of High-Speed Railway Based on LightGBM Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Bing Wang ◽  
Peixiu Wu ◽  
Quanchao Chen ◽  
Shaoquan Ni
Keyword(s):  
Prediction Accuracy ◽  
High Speed ◽  
Influence Factor ◽  
Flow Time ◽  
Time Sequence ◽  
Load Factor ◽  
High Speed Railway ◽  
Passenger Flow ◽  
Weather Factor ◽  
Passenger Load Factor

In order to improve the prediction accuracy of train passenger load factor of high-speed railway and meet the demand of different levels of passenger load factor prediction and analysis, the influence factor of the train passenger load factor is analyzed in depth. Taking into account the weather factor, train attribute, and passenger flow time sequence, this paper proposed a forecasting method of train passenger load factor of high-speed railway based on LightGBM algorithm of machine learning. Considering the difference of the influence factor of the passenger load factor of a single train and group trains, a single train passenger load factor prediction model based on the weather factor and passenger flow time sequence and a group of trains’ passenger load factor prediction model based on the weather factor, the train attribute, and passenger flow time sequence factor were constructed, respectively. Taking the train passenger load factor data of high-speed railway in a certain area as an example, the feasibility and effectiveness of the proposed method were verified and compared. It is verified that LightGBM algorithm of machine learning proposed in this paper has higher prediction accuracy than the traditional models, and its scientific and accurate prediction can provide an important reference for the calculation of passenger ticket revenue, operation benefit analysis, etc.

Optimal Allocation of High-Speed Railway Mobile Equipment Based on the Passenger Flow

2014 ◽  
Vol 505-506 ◽  
pp. 471-476
Author(s):  
Qing Jie Zheng ◽  
Bao Ming Han ◽  
Hua Li
Keyword(s):  
High Speed ◽  
Optimal Allocation ◽  
Allocation Problem ◽  
Load Factor ◽  
Transport Capacity ◽  
High Speed Railway ◽  
Passenger Flow ◽  
The Relationship ◽  
Passenger Load Factor ◽  
Multiple Units

Based on the relationship between passenger flow and demand of electric multiple units (EMU), a new methodology to calculate the EMU demand and allocate the EMU is proposed, which can meet the demand of passenger as well as avoid the waste of transport capacity. An offline allocation plan of EMU is designed by analyzing the fluctuation in passenger flow, passenger average haul distance, passenger load factor and so on. Using the methodology, the EMU allocation problem is solved through program, which is used in Beijing-Shanghai High-speed Railway to obtain the EMU allocation plan.

Application Research on Revenue Management in China High Speed Railway

2010 ◽  
Author(s):  
ChunYan Li ◽  
MinShu Ma ◽  
XiaoJun Li
Keyword(s):  
Revenue Management ◽  
High Speed ◽  
Load Factor ◽  
Application Research ◽  
Long Distance ◽  
High Speed Railway ◽  
Passenger Flow ◽  
Sales Process ◽  
Railway Industry

Revenue management in the modern railway industry has been more and more applications. To achieve the desired results, the specific application environment must be considered. The features of China’s railway are discussed firstly, and then a method of seats allotment with objective to maximize the seat load factor is proposed to increase revenue. This method is adapted to multi seat classes on multi segments under the condition of fares relative fixed in China and also meet the need of opening pricing in future. The train T15 is chosen as the object for illustrative analysis, and the result indicate that the method is useful to improve the seat load factor. Additionally it is also effective to make the seats more in line with the trends of passenger flow, and reduce the probability and amount of long-distance tickets randomly cutting into short ones in the sales process.

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 Evaluation of Dynamic Load Factors for a High-Speed Railway Truss Arch Bridge

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Ding Youliang ◽  
Wang Gaoxin
Keyword(s):  
Finite Element ◽  
Dynamic Load ◽  
High Speed ◽  
Field Monitoring ◽  
Generalized Extreme Value Distribution ◽  
Monitoring Data ◽  
Load Factor ◽  
High Speed Railway ◽  
Arch Bridge ◽  
The Impact

Studies on dynamic impact of high-speed trains on long-span bridges are important for the design and evaluation of high-speed railway bridges. The use of the dynamic load factor (DLF) to account for the impact effect has been widely accepted in bridge engineering. Although the field monitoring studies are the most dependable way to study the actual DLF of the bridge, according to previous studies there are few field monitoring data on high-speed railway truss arch bridges. This paper presents an evaluation of DLF based on field monitoring and finite element simulation of Nanjing DaShengGuan Bridge, which is a high-speed railway truss arch bridge with the longest span throughout the world. The DLFs in different members of steel truss arch are measured using monitoring data and simulated using finite element model, respectively. The effects of lane position, number of train carriages, and speed of trains on DLF are further investigated. By using the accumulative probability function of the Generalized Extreme Value Distribution, the probability distribution model of DLF is proposed, based on which the standard value of DLF within 50-year return period is evaluated and compared with different bridge design codes.

Key Issues on Train Line Planning for Beijing-Shanghai High Speed Railway

2010 ◽  
Author(s):  
L. Nie ◽  
D. B. Fei ◽  
S. D. Zhou ◽  
H. L. Fu ◽  
L. Tong
Keyword(s):  
High Frequency ◽  
High Speed ◽  
Travel Demand ◽  
Time Window ◽  
Long Distance ◽  
Line Planning ◽  
High Speed Railway ◽  
Passenger Flow ◽  
Train Operation ◽  
Service Plan

The Beijing-Shanghai High speed railway line (Hereinafter referred to as “Jing-Hu HSL”) is one of the most important railway lines in the Chinese rapid passenger transportation network and will be put into operation at the end of 2011. Train line planning directly reflects the quality and competition ability of train services. The characteristics of operational conditions and passenger flow of this corridor HSL bring about a few new issues on train line planning like night train operation, train OD sets, cyclic operation, and train stop schedule. For the first issue, a large amount of long distance travel demand put forward the demand for night services, which causes great conflict with the time-window for maintenance work. The confliction can be solved by harmoniously utilizing the parallel lines. For the second one, in view of the differences of technical and economic factors between HSL and conventional railways, high frequency and medium-long distance train will dominate HSL’s train service plan rather than low frequency and long distance trains on conventional railways. Thus, part of long-distance passenger flow has to transfer at some stations. Considering the whole possible ODs over Jing-Hu HSL and the transfer condition of related stations, the optimal OD sets and corresponding transfer plan is suggested. High frequency makes HSL possible to operate trains cyclically to improve service quality. However, with too many train ODs and some special trains, e.g. night train, an incomplete cyclic train operation mode is more practical. The ODs which can provide cyclic service for Jing-Hu HSL need to be identified. For the last issue, although non-stop long-distance train is a very popular kind of service in China, it should be reconsidered for Jing-Hu HSL line because of massive intercity travel demand and regular stops required. Each of the above issues is very complex. What is more, they have close relationship between each other. Due to limited space, the methods used to solve these issues are given in conceptual way rather than detailed description of mathematical model. The research paves the way for future integration study to design an efficient, economic, convenient, and regular train service plan for Jing-Hu HSL.

Sign in / Sign up

Export Citation Format

Share Document