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dc.contributor.author김선우-
dc.date.accessioned2019-10-17T05:59:33Z-
dc.date.available2019-10-17T05:59:33Z-
dc.date.issued2019-05-
dc.identifier.citationIEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, v. 68, NO 5, Page. 4105-4109en_US
dc.identifier.issn0018-9545-
dc.identifier.issn1939-9359-
dc.identifier.urihttps://ieeexplore.ieee.org/document/8723487-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/111192-
dc.description.abstractThe articles in this special section focuses on Vehicle (IoV) technologies and applications. With the significant development of smart vehicles, IoV technologies have received widespread attention. The IoV technology refers to dynamic mobile communication systems that communicate between vehicles and public networks using V2V (vehicle-to-vehicle),V2R (vehicle-to-road), V2H (vehicle-to-human) and V2S (vehicleto- sensor) interactions. It enables information sharing and the gathering of information on vehicles, roads, and their surrounds. The actual applications of smart Vehicles and IoV systems meet with many challenges, such as how the big data in IoV can be collected and distributed to the interested vehicles and human beings for the purpose of enhancing the road users’ experience, how huge volumes of data can be processed toward reducing the road congestion and improving traffic management and road safety, how to realize quick and efficient communication between a large amount of different kinds of vehicles and smart devices, how to effectively process the large collections of data in IoV systems, or how to protect the privacy. Many machine learning methods can be used With the significant development of smart vehicles, Internet of Vehicle (IoV) technologies have received widespread attention. The IoV technology refers to dynamic mobile communication systems that communicate between vehicles and public networks using V2V (vehicle-to-vehicle),V2R (vehicle-to-road), V2H (vehicle-to-human) and V2S (vehicleto- sensor) interactions. It enables information sharing and the gathering of information on vehicles, roads, and their surrounds. The actual applications of smart Vehicles and IoV systems meet with many challenges, such as how the big data in IoV can be collected and distributed to the interested vehicles and human beings for the purpose of enhancing the road users’ experience, how huge volumes of data can be processed toward reducing the road congestion and improving traffic management and road safety, how to realize quick and efficient communication between a large amount of different kinds of vehicles and smart devices, how to effectively process the large collections of data in IoV systems, or how to protect the privacy. Many machine learning methods can be useden_US
dc.language.isoenen_US
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCen_US
dc.subjectSpecial issues and sectionsen_US
dc.subjectIntelligent vehiclesen_US
dc.subjectLearning systemsen_US
dc.subjectSmart devicesen_US
dc.subjectNeural networksen_US
dc.subjectVehicle dynamicsen_US
dc.subjectMathematical modelen_US
dc.subjectVehicular ad hoc networksen_US
dc.subjectVehicle-to-everythingen_US
dc.titleGuest Editorial: Introduction to the Special Section on Machine Learning-Based Internet of Vehicles: Theory, Methodology, and Applicationsen_US
dc.typeArticleen_US
dc.relation.no5-
dc.relation.volume68-
dc.identifier.doi10.1109/TVT.2019.2914747-
dc.relation.page4105-4109-
dc.relation.journalIEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY-
dc.contributor.googleauthorGuo, Jun-
dc.contributor.googleauthorKim, Sunwoo-
dc.contributor.googleauthorWymeersch, Henk-
dc.contributor.googleauthorSaad, Walid-
dc.contributor.googleauthorChen, Wei-
dc.relation.code2019003055-
dc.sector.campusS-
dc.sector.daehakCOLLEGE OF ENGINEERING[S]-
dc.sector.departmentDEPARTMENT OF ELECTRONIC ENGINEERING-
dc.identifier.pidremero-
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COLLEGE OF ENGINEERING[S](공과대학) > ELECTRONIC ENGINEERING(융합전자공학부) > Articles
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