Please use this identifier to cite or link to this item: http://repository.kln.ac.lk/handle/123456789/19030
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dc.contributor.authorIfthikar, A.-
dc.contributor.authorHettiarachchi, S.-
dc.date.accessioned2018-08-17T05:54:24Z-
dc.date.available2018-08-17T05:54:24Z-
dc.date.issued2018-
dc.identifier.citationIfthikar,A. and Hettiarachchi,S. (2018). Analysis of historical accident data to determine accident prone locations and cause of accidents. International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka. p.182.en_US
dc.identifier.urihttp://repository.kln.ac.lk/handle/123456789/19030-
dc.description.abstractRoad traffic accidents causes great distress and destroy the lives of many individuals. Inspite of different attempts to solve this problem, it still resides as a major cause of death. This paper proposes a system to analyse historical accident data and subsequently identify accident-prone areas and their relevant causes via clustering accident location coordinates. This system, once developed, can be used to warn drivers and also to aid fully autonomous automobiles to take precautions at accident-prone areas.en_US
dc.language.isoenen_US
dc.publisherInternational Research Conference on Smart Computing and Systems Engineering - SCSE 2018en_US
dc.subjectAutonomous automobilesen_US
dc.subjectClustering algorithmsen_US
dc.subjectData miningen_US
dc.subjectGlobal positioning systemen_US
dc.subjectRoad traffic accidentsen_US
dc.titleAnalysis of historical accident data to determine accident prone locations and cause of accidentsen_US
dc.typeArticleen_US
Appears in Collections:Smart Computing and Systems Engineering - 2018 (SCSE 2018)

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