dc.creatorKviesis, Armands
dc.creatorZacepins, Aleksejs
dc.creatorKomasilovs, Vitalijs
dc.creatorMunizaga, Marcela
dc.date.accessioned2019-05-31T15:21:06Z
dc.date.available2019-05-31T15:21:06Z
dc.date.created2019-05-31T15:21:06Z
dc.date.issued2018
dc.identifierVEHITS 2018 - Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems, 2018
dc.identifierhttps://repositorio.uchile.cl/handle/2250/169503
dc.description.abstractAll rights reserved. The increase of population has intensified everyday rush. Traffic congestions are still a problem in cities and are one of the main cause for public transport delays. City residents and visitors have experienced time loss by using public transport buses, because of waiting at the bus stops and not knowing if the bus is delayed or already serviced the stop. Therefore it is valuable for people to know at what time the bus should arrive (or is it already missed) at specific bus stop. Real-time public bus tracking and management system development has been the focus of many researchers, and many studies have been done in this area. This paper focuses on bus travel time prediction comparison between linear regression and support vector regression models (SVR), when using limited data set.
dc.languageen
dc.publisherSciTePress
dc.sourceVEHITS 2018 - Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems
dc.subjectArrival Time
dc.subjectGPS Data
dc.subjectPublic Buses
dc.subjectSmart Public Transport
dc.titleBus arrival time prediction with limited data set using regression models
dc.typeArtículo de revista


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