Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/9025
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dc.contributor.authorKosmides, Pavlos-
dc.contributor.authorLambrinos, Lambros-
dc.contributor.authorAsthenopoulos, Vasilis-
dc.contributor.authorDemestichas, Konstantinos-
dc.contributor.authorAdamopoulou, Evgenia-
dc.contributor.otherΚοσμίδης, Παύλος-
dc.contributor.otherΛαμπρινός, Λάμπρος-
dc.date.accessioned2017-01-13T10:55:10Z-
dc.date.available2017-01-13T10:55:10Z-
dc.date.issued2016-08-15-
dc.identifier.citationIEEE Symposium on Computers and Communications, 2016, Messina, Italyen_US
dc.identifier.isbn978-150900679-3-
dc.identifier.urihttp://ktisis.cut.ac.cy/handle/10488/9025-
dc.description.abstractOne of the most significant issues the research community has focused on during the last decades, is the reduction of the energy consumed in every aspect of everyday life. A standout amongst the most important factors of energy consumption is transportation. To this end, a lot of work in the field of Intelligent Transport Systems concentrates on enhancing energy efficiency. This trend was reinforced by the appearance of Fully Electric Vehicles (FEVs), where it is more crucial to increase their energy efficiency in any manner. Eco-routing refers to the choice of the most energy efficient route towards a destination and seems very promising for reducing everyday energy consumption. In this paper, we present a novel method for predicting energy consumption levels, based on machine learning techniques. In addition, addressing the problem of ever increasing amounts of tracking data acquired from vehicles, we introduce a clustering based prediction method and apply it on real world measurements in order to evaluate its performance.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.rights© 2016 IEEEen_US
dc.subjectClustering based predictionen_US
dc.subjectEnergy efficiencyen_US
dc.subjectIntelligent Transport Systemsen_US
dc.subjectMachine learningen_US
dc.titleA clustering based approach for energy efficient routingen_US
dc.typeConference Papersen_US
dc.doi10.1109/ISCC.2016.7543745en_US
dc.collaborationCyprus University of Technologyen_US
dc.collaborationNational Technical University Of Athensen_US
dc.subject.categoryCivil Engineeringen_US
dc.subject.categoryCivil Engineeringen_US
dc.journalsSubscription Journalen_US
dc.countryCyprusen_US
dc.countryGreeceen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.languageiso639-1other-
crisitem.author.deptDepartment of Communication and Internet Studies-
crisitem.author.deptDepartment of Communication and Internet Studies-
crisitem.author.facultyFaculty of Communication and Media Studies-
crisitem.author.facultyFaculty of Communication and Media Studies-
crisitem.author.parentorgFaculty of Communication and Media Studies-
crisitem.author.parentorgFaculty of Communication and Media Studies-
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers
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