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dc.contributor.authorSingh, Nitesh
dc.contributor.authorBhatia, Mohit
dc.date.accessioned2024-09-20T08:04:57Z
dc.date.available2024-09-20T08:04:57Z
dc.date.issued2023-04
dc.identifier.urihttp://10.10.11.6/handle/1/18245
dc.descriptionSCHOOL OF COMPUTING SCIENCE AND ENGINEERING DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING / DEPARTMENT OF COMPUTERAPPLICATION GALGOTIAS UNIVERSITY, GREATER NOIDA INDIAen_US
dc.description.abstractThe traffic flow prediction is an essential part of a city transportation system. With people relying on various modes of transportation, traffic in big cities is increasing at an exponential rate. In this scenario, prediction of traffic flow becomes very important not only for the administration but also for the common man travelling on the road. For this reason, various traffic flow prediction systems based on machine learning algorithms have been proposed in the past few years. However, accuracy of such systems is still a big concern. Also, the parameters considered for predicting traffic flow have not been very comprehensive in nature.en_US
dc.language.isoen_USen_US
dc.publisherGalgotias Universityen_US
dc.subjectTraffic Flowen_US
dc.subjectMachine Learningen_US
dc.titleTraffic Flow Prediction using Machine Learningen_US
dc.typeTechnical Reporten_US


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