Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/4808
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dc.contributor.authorÖzuysal, Mustafa-
dc.contributor.authorTayfur, Gökmen-
dc.contributor.authorTanyel, Serhan-
dc.date.accessioned2017-02-08T08:08:17Z
dc.date.available2017-02-08T08:08:17Z
dc.date.issued2012
dc.identifier.citationÖzuysal, M., Tayfur, G., and Tanyel, S. (2012). Passenger flows estimation of light rail transit (LRT) system in İzmir, Turkey using multiple regression and ann methods. Promet - Traffic&Transportation, 24(1), 1-14.en_US
dc.identifier.issn0353-5320
dc.identifier.issn0353-5320-
dc.identifier.urihttp://hdl.handle.net/11147/4808
dc.description.abstractPassenger flow estimation of transit systems is essential for new decisions about additional facilities and feeder lines. For increasing the efficiency of an existing transit line, stations which are insufficient for trip production and attraction should be examined first. Such investigation supports decisions for feeder line projects which may seem necessary or futile according to the findings. In this study, passenger flow of a light rail transit (LRT) system in Izmir, Turkey is estimated by using multiple regression and feed-forward back-propagation type of artificial neural networks (ANN). The number of alighting passengers at each station is estimated as a function of boarding passengers from other stations. It is found that ANN approach produced significantly better estimations specifically for the low passenger attractive stations. In addition, ANN is found to be more capable for the determination of trip-attractive parts of LRT lines.en_US
dc.language.isoenen_US
dc.publisherFaculty of Transport and Traffic Sciences, University of Zagreben_US
dc.relation.ispartofPromet - Traffic - Trafficoen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectArtificial neural networksen_US
dc.subjectLight rail transiten_US
dc.subjectMultiple regressionen_US
dc.subjectPublic transportationen_US
dc.subjectIzmiren_US
dc.titlePassenger flows estimation of light rail transit (LRT) system in Izmir, Turkey using multiple regression and ann methodsen_US
dc.title.alternativeÇoklu regresyon ve yapay si̇ni̇r aǧları (YSA) yöntemleri̇ kullanılarak İzmi̇r-Türki̇ye'deki̇ hafi̇f rayli si̇steme (HRS) ai̇t yolcu akımlarının modellenmesi̇en_US
dc.typeArticleen_US
dc.authoridTR2054en_US
dc.departmentIzmir Institute of Technology. Civil Engineeringen_US
dc.identifier.volume24en_US
dc.identifier.issue1en_US
dc.identifier.startpage1en_US
dc.identifier.endpage14en_US
dc.identifier.wosWOS:000301566300001
dc.identifier.scopusSCOPUS:2-s2.0-84937346379
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
item.fulltextWith Fulltext-
item.cerifentitytypePublications-
item.grantfulltextopen-
crisitem.author.deptDepartment of Computer Engineering-
crisitem.author.deptDepartment of Civil Engineering-
Appears in Collections:Civil Engineering / İnşaat Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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