Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/80018
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dc.contributorDepartment of Civil and Environmental Engineering-
dc.creatorYuan, Y-
dc.creatorShao, C-
dc.creatorZhang, S-
dc.creatorMei L-
dc.date.accessioned2018-12-21T07:14:40Z-
dc.date.available2018-12-21T07:14:40Z-
dc.identifier.issn1755-1307-
dc.identifier.urihttp://hdl.handle.net/10397/80018-
dc.description2018 2nd International Symposium on Resource Exploration and Environmental Science, REES 2018, 28-29 April 2018en_US
dc.language.isoenen_US
dc.publisherInstitute of Physics Publishingen_US
dc.rightsContent from this work may be used under the terms of the Creative Commons Attribution 3.0 licence (https://creativecommons.org/licenses/by/3.0/). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.en_US
dc.rightsPublished under licence by IOP Publishing Ltden_US
dc.rightsThe following publication Yuan, Y., Shao, C., Zhang, S., & Mei, L. (2018). Genetic and simulated annealing algorithms-based traffic state identification. IOP conference series : earth and environmental science, 2018, 170 (2), 32117, 1-12 is available at https://dx.doi.org/10.1088/1755-1315/170/3/032117en_US
dc.titleGenetic and simulated annealing algorithms-based traffic state identificationen_US
dc.typeConference Paperen_US
dc.identifier.spage1-
dc.identifier.epage12-
dc.identifier.volume170-
dc.identifier.issue2-
dc.identifier.doi10.1088/1755-1315/170/3/032117-
dcterms.abstractAccurate and scientific traffic state identification is the basis of traffic navigation system, traffic control system and traffic organization optimization. In this paper, the dynamic traffic data collected by geomagnetic detector are firstly used to identify traffic state. We proposed SAGA-FCM clustering algorithm which is combined simulated annealing algorithm (SA) with genetic algorithm (GA) for urban expressway traffic state identification. This method can overcome the problems those the dynamic data of other detectors are not accurate and the time interval is not uniform. Meanwhile, it can overcome the instability of FCM algorithm clustering center and it is easy to fall into the local extreme value and "premature" problem of genetic algorithm. Research results show that, Compared with FCM algorithm and GA-FCM algorithm, SAGA-FCM clustering algorithm can be more effective and fast convergence, so as to improve the accuracy of urban traffic state identification.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIOP conference series : earth and environmental science, 2018, v. 170, no. 2, 32117, p. 1-12-
dcterms.isPartOfIOP conference series : earth and environmental science-
dcterms.issued2018-
dc.identifier.scopus2-s2.0-85051976928-
dc.relation.conferenceInternational Symposium on Resource Exploration and Environmental Science [REES]-
dc.identifier.artn32117-
dc.description.validate201812 bcrc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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