Stations, trains and small-world networks

By Katherine A. Seaton, Luke Hackett. 2003

210 citations recorded by the source corpus.

The clustering coefficient, path length and average vertex degree of two urban train line networks have been calculated. The results are compared with theoretical predictions for appropriate random bipartite graphs. They have also been compared with one another to investigate the effect of architecture on the small-world properties.

Subfields: Artificial Intelligence, Statistical and Nonlinear Physics, Signal Processing

View Paper: https://www.semanticscholar.org/paper/9812b5fc3c8f76b0021ac8097bb833f0bccfba4b

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In Artificial Intelligence

In Statistical and Nonlinear Physics

In Signal Processing

Citations in the corpus

Layered complex networks. (2005, methodology): “The graphs based on the physical infrastructure of such networks were analyzed on the examples of a power grid [5, 6], railway network [7], road networks [8, 9], or urban mass transportation systems [10, 11, 12, 13].”
Analysis of Public Bus Transportation of a Brazilian City Based on the Theory of Complex Networks Using the P-Space (2016, unknown): “Also urban train networks of Vienna (Austria) and Boston (USA) were analyzed by extending the use of random bipartite graph models from social networks to technological ones [7].”
Analyzing and modeling real-world phenomena with complex networks: a survey of applications (2007, background): “Therefore, we shall not d iscuss networks such as the railways [303, 304, 305], subway networks [306], and public tran sportation [307, 308, 309].”