A variant of the current flow betweenness centrality and its application in urban networks

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Title: A variant of the current flow betweenness centrality and its application in urban networks
Authors: Agryzkov, Taras | Tortosa, Leandro | Vicent, Jose F.
Research Group/s: Análisis y Visualización de Datos en Redes (ANVIDA)
Center, Department or Service: Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial
Keywords: Urban centrality measures | Random-walk betweenness | Current flow betweenness | Spatial networks | Urban networks
Knowledge Area: Ciencia de la Computación e Inteligencia Artificial
Issue Date: 15-Apr-2019
Publisher: Elsevier
Citation: Applied Mathematics and Computation. 2019, 347: 600-615. doi:10.1016/j.amc.2018.11.032
Abstract: The current flow betweenness centrality is a useful tool to estimate traffic status in spatial networks and, in general, to measure the intermediation of nodes in networks where the transition between them takes place in a random way. The main drawback of this centrality is its high computational cost, especially for very large networks, as it is the case of urban networks. In this paper, a new approach to the current flow betweenness centrality for its practical application in urban networks with data is presented and discussed. The new centrality measure allows the estimation of pedestrian flow developed in urban networks, taking into account both the network topology and its associated data. In addition, its computational cost makes it suitable for application in networks with a large number of nodes. Some examples are studied in order to better understand the characteristics and behaviour of the proposed centrality in the context of the city.
Sponsor: Partially supported by the Spanish Government, Ministerio de Economía y Competividad, grant number TIN2017-84821-P .
URI: http://hdl.handle.net/10045/87150
ISSN: 0096-3003 (Print) | 1873-5649 (Online)
DOI: 10.1016/j.amc.2018.11.032
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2018 Elsevier Inc.
Peer Review: si
Publisher version: https://doi.org/10.1016/j.amc.2018.11.032
Appears in Collections:INV - ANVIDA - Artículos de Revistas

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