Measuring Method of Node Importance of Urban Rail Network Based on H Index
Source abstract
Abstract
Urban rail stations play an important role in passenger distribution and connectivity intervals in the network. How to effectively and reasonably evaluate their importance in the network is the key to optimizing the urban rail network structure and reducing operational risks. Taking the site as the research object and considering the topology, passenger volume, and passenger flow correlation of the urban rail network, the index of citation index is used to define node importance metric based on the h-index. Furthermore, the method of calculating the importance degree of urban rail transit network nodes based on h-index is proposed. The validity of the method is verified by the data of Beijing urban rail network in 2016, and the results are compared with the existing central index based on the network topology characteristics.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Human Mobility and Location-Based Analysis · Transportation Planning and Optimization · Complex Network Analysis Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China
Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China
Funding
National Science Foundation of China · Fundamental 355 Research Funds for the Central Universities
References (21)
Show source-provided references
1. Vulnerability analysis of urban rail transit based on complex network theory: A case study of shanghai metro10.1007/s12469-017-0170-2 ↗
2. Transportation functionality vulnerability of urban rail transit networks based on movingblock: The case of Nanjing metro10.1016/j.physa.2019.122367 ↗
3. Cascading failure analysis and robustness optimization of metro networks based on coupled map lattices: a case study of Nanjing, China
4. Empirical analysis of a scale-free railway network in china10.1016/j.physa.2007.04.031 ↗
5. Complex Network Topology of Transportation Systems
6. Networked analysis of the shanghai subway network, in china10.1016/j.physa.2011.06.022 ↗
7. Characteristics on hub networks of urban rail transit networks10.1016/j.physa.2015.12.060 ↗
8. Discovery of Critical Nodes in Road Networks Through Mining From Vehicle Trajectories10.1109/TITS.2018.2817282 ↗
9. The influence of passenger flow on the topology characteristics of urban rail transit networks10.1142/S0217979217501818 ↗
10. An algorithm for ranking the nodes of an urban network based on the concept of PageRank vector
11. New highlights and a new centrality measure based on the Adapted PageRank Algorithm for urban networks
12. An index to quantify an individual’s scientific research output10.1073/pnas.0507655102 ↗
13. Topological structure and the h index in complex networks10.1103/PhysRevE.95.022301 ↗
14. The h-index of a network node and its relation to degree and coreness10.1038/ncomms10168 ↗
15. Approach based h-index to measuring the important classes in software network
16. A method of node importance measurement in software network based on the variations of h-index
17. Theory and practise of the g-index10.1007/s11192-006-0144-7 ↗
18. Hillier, B., and Hanson, J. (1984). The Social Logic of Space, Cambridge University Press.10.1017/CBO9780511597237 ↗
19. Blanchard, P., and Volchenkov, D. (2009). Mathematical Analysis of Urban Spatial Networks, Springer.10.1007/978-3-540-87829-2 ↗
20. Graph-theory
21. Abbas, A.M. (2012). Bounds and inequalities relating h-index, g-index, e-index and generalized impact factor: An improvement over existing models. PLoS ONE, 7.10.1371/journal.pone.0033699 ↗