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 |