Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/16721
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dc.contributor.authorGegov, E-
dc.contributor.authorGegov, A-
dc.contributor.authorPostorino, MN-
dc.contributor.authorAtherton, M-
dc.contributor.authorGobet, F-
dc.date.accessioned2018-08-14T11:04:53Z-
dc.date.available2012-01-01-
dc.date.available2018-08-14T11:04:53Z-
dc.date.issued2012-
dc.identifier.citationIFAC Proceedings Volumes (IFAC-PapersOnline), 2012, 45 (24), pp. 1 - 6en_US
dc.identifier.issn1474-6670-
dc.identifier.issnhttp://dx.doi.org/10.3182/20120912-3-BG-2031.00001-
dc.identifier.issnhttp://dx.doi.org/10.3182/20120912-3-BG-2031.00001-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/16721-
dc.description.abstractThis article presents an evolution-based model for the US airport network. The topological properties and the volume of people travelling are both studied in detail, revealing high heterogeneity in space and time. A recently developed community structure detection method, accounting for the spatial nature of these networks, reveals a better picture of the communities within. © 2012 IFAC.en_US
dc.format.extent1 - 6-
dc.language.isoenen_US
dc.publisherInternational Federation of Automatic Controlen_US
dc.subjectair transportationen_US
dc.subjectcommunity structureen_US
dc.subjectUnited States Airport Networken_US
dc.titleSpace-independent community structure detection in United States air transportationen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.3182/20120912-3-BG-2031.00001-
dc.relation.isPartOfIFAC Proceedings Volumes (IFAC-PapersOnline)-
pubs.issue24-
pubs.publication-statusPublished-
pubs.volume45-
Appears in Collections:Dept of Mechanical and Aerospace Engineering Research Papers

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