Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9896
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dc.contributor.authorPathania, Ayush-
dc.contributor.authorVyas, Devesh-
dc.contributor.authorGoel, Shubham [Guided by]-
dc.date.accessioned2023-09-08T12:07:15Z-
dc.date.available2023-09-08T12:07:15Z-
dc.date.issued2023-
dc.identifier.urihttp://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9896-
dc.descriptionEnrolment No. 191249, 191248en_US
dc.description.abstractIn urban areas, obstruction is a difficult problem to manage since the number of automobiles continually rises faster than the traffic infrastructure that can sustain them. In the case of fender benders, it gets considerably more scary. Several facets of modern life are affected by this issue, including financial results, traffic accidents, the expansion of nursery outflows, time spent, and health issues. Modern cultures may rely on the flow of traffic the board structure in this particular situation to prevent congestion and its unfavourable effects. In order to improve overall traffic competence and the health of the transportation systems, traffic the board frameworks are composed of a variety of executive and user tools. In addition, to deal with this issue, the traffic executive structure gathers information from a variety of sources, analyses this information to determine risks that could reduce traffic competence, and then offers a variety of forms of assistance to control those risks.en_US
dc.language.isoen_USen_US
dc.publisherJaypee University of Information Technology, Solan, H.P.en_US
dc.subjectTraffic managementen_US
dc.subjectNeural networken_US
dc.subjectMachine learningen_US
dc.titleDynamic Traffic Management Systemen_US
dc.typeProject Reporten_US
Appears in Collections:B.Tech. Project Reports

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