Interurban rail network robustness analysis: Case study of Iran

Author(s):  
Navid Khademi ◽  
Mohsen Babaei ◽  
Amirhossein Fani
Author(s):  
J. Ackermann ◽  
H.Z. Hu ◽  
D. Kaesbauer
Keyword(s):  

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Qing Cai ◽  
Mahardhika Pratama ◽  
Sameer Alam

Complex networks in reality may suffer from target attacks which can trigger the breakdown of the entire network. It is therefore pivotal to evaluate the extent to which a network could withstand perturbations. The research on network robustness has proven as a potent instrument towards that purpose. The last two decades have witnessed the enthusiasm on the studies of network robustness. However, existing studies on network robustness mainly focus on multilayer networks while little attention is paid to multipartite networks which are an indispensable part of complex networks. In this study, we investigate the robustness of multipartite networks under intentional node attacks. We develop two network models based on the largest connected component theory to depict the cascading failures on multipartite networks under target attacks. We then investigate the robustness of computer-generated multipartite networks with respect to eight node centrality metrics. We discover that the robustness of multipartite networks could display either discontinuous or continuous phase transitions. Interestingly, we discover that larger number of partite sets of a multipartite network could increase its robustness which is opposite to the phenomenon observed on multilayer networks. Our findings shed new lights on the robust structure design of complex systems. We finally present useful discussions on the applications of existing percolation theories that are well studied for network robustness analysis to multipartite networks. We show that existing percolation theories are not amenable to multipartite networks. Percolation on multipartite networks still deserves in-depth efforts.


Author(s):  
Zhenhua Chen

In this study, we focus on the Acela Express, and try to find out how selected internal and external factors affect the Acela Express’s ridership. A two-stage least square regression model is introduced in order to eliminate the endogeneity problem caused by price and ridership. Also the Cochrane-Orcutt Procedure is adopted to solve autocorrelation. The result shows that ticket price and train on-time performances, which are used to being thought as important factors affect ridership become insignificant, while other factors like employment of business and professional in the Northeast Corridor areas have higher influence on high speed train ridership. The broader objective of this research is to provide policy suggestions for building of an efficient high-speed rail network that can both be profitable and solve practical problems that the contemporary transportation system faces.


AIP Advances ◽  
2018 ◽  
Vol 8 (7) ◽  
pp. 075219 ◽  
Author(s):  
Shuliang Wang ◽  
Sen Nie ◽  
Longfeng Zhao ◽  
H. Eugene Stanley

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Lu Zhang ◽  
Yannan Zhao ◽  
Dongli Chen ◽  
Xinhuan Zhang

Aviation transport is one of the most important and critical infrastructures in today’s global economy. Failure in its proper operations can seriously impact regional economic development, which is why it is important to evaluate network robustness. Previous analyses of robustness have mainly been conducted with an unweighted approach. In the development of air transport, however, the demand for route configuration has gradually decreased, while the demand for flight adjustments has increased. Consequently, the aviation network has developed unevenly, so adhering to a uniform approach for evaluating network robustness may lead to inaccurate results. Therefore, we examined which centrality sequence is the most sensitive to network robustness in both unweighted and weighted approaches. The air transport network selected for the case study comprised the six subregions of the Eurasian landmass of the Belt and Road region. The study results showed the following: (a) in the network constructed as an unweighted one, betweenness, and degree centrality had higher priorities in preserving network functionalities than eigenvector and closeness centrality; (b) in the network constructed as a weighted one, recursive power had a higher priority in preserving network functionalities than recursive centrality; and (c) no particular centrality measurement had a significant advantage in representing the totality of robustness. The betweenness centrality sequence was sensitive to the average shortest path length and global efficiency; the recursive power sequence was sensitive to the clustering coefficient, while degree centrality was sensitive to graph diversity. The findings of this study support the decisions about managing air transportation in the Belt and Road region.


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