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Article
Using Data Mining Technique to Predict Cause of Accident and Accident Prone Locations on Highway
American Journal of Database Theory and Application (2012)
  • Dr. Dipo Theophilus Akomolafe, MBCS, MNCS, MCPN,
Abstract

Road accident is a special case of trauma that constitutes a major cause of disability, untimely death and loss of loved ones as well as family bread winners. Therefore, predicting the likelihood of road accident on high ways with particular emphasis on Lagos – Ibadan express road, Nigeria in order to prevent accident is very important. Various attempts had been made to identify the cause(s) of accidents on highways using different techniques and system and to reduce accident on the roads but the rate of accident keep on increasing. In this study, the various techniques used to analyse the causes of accidents along this route and the effects of accidents were examined. A technique of using data mining tool to predict the likely occurrence of accident on highways, the likely cause of the accident and accident prone locations was proposed using Lagos –Ibadan highway as a case study. WEKA software was used to analyse accident data gathered along this road. The results showed that causes of accidents, specific time/condition that could trigger accident and accident prone areas could be effectively identified.

Keywords
  • Data Mining,
  • Decision Tree,
  • Accident,
  • WEKA,
  • Data Modelling,
  • Id3 Algorith m,
  • Id 3 Tree,
  • Functional Tree
Publication Date
2012
Citation Information
Dr. Dipo Theophilus Akomolafe. "Using Data Mining Technique to Predict Cause of Accident and Accident Prone Locations on Highway" American Journal of Database Theory and Application Vol. 1 Iss. 3 (2012)
Available at: http://works.bepress.com/drdipo_akomolafe/1/