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Analysis of Historical Accident Data to Determine Accident Prone Locations and Cause of Accidents

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dc.contributor.author Ifthikar, Arshardh
dc.contributor.author Hettiarachchi, Saman
dc.date.accessioned 2020-05-27T17:37:57Z
dc.date.available 2020-05-27T17:37:57Z
dc.date.issued 2018
dc.identifier.citation Ifthikar, A and Hettiarachchi, S (2018) ‘Analysis of Historical Accident Data to Determine Accident Prone Locations and Cause of Accidents’ In: 2018 8th International Conference on Intelligent Systems, Modelling and Simulation (ISMS), Kuala Lumpur, Malaysia. 8-10 May 2018. pp. 11-15 IEEE DOI: 10.1109/ISMS.2018.00012 en_US
dc.identifier.uri https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8699325
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/444
dc.description.abstract Road traffic accidents is a severe issue which causes great distress and destroys lives of many individuals. In spite of different attempts to solve this problem, it still resides as a major cause of death. This paper discusses several attempts made to identify causes for road accidents. Finally, a system is proposed to analyze 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.publisher IEEE en_US
dc.subject Data Mining en_US
dc.subject Road Traffic Accidents en_US
dc.subject Clustering Algorithms en_US
dc.subject Entropy en_US
dc.subject Clustering algorithms en_US
dc.title Analysis of Historical Accident Data to Determine Accident Prone Locations and Cause of Accidents en_US
dc.type Article en_US


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