open access

A Comparative Analysis of Heterogeneity In Road Accident Data Using Data Mining Techniques

  • Anitha S Student, Department of IT, K.S. Rangasamy College of Technology, Tiruchengode, Tamilnadu, India
  • Keerthana R Student, Department of IT, K.S. Rangasamy College of Technology, Tiruchengode, Tamilnadu, India
  • Pavithra B Student, Department of IT, K.S. Rangasamy College of Technology, Tiruchengode, Tamilnadu, India
  • Sangeetha M Assistant Professor, Department of IT, K.S. Rangasamy College of Technology, Tiruchengode, Tamilnadu, India

Abstract

Road accidents are one of the most imperative factors that affect the untimely death among people and economic loss of public and private property. Road safety is a term associated with the planning and implementing certain strategy to overcome the road and traffic accidents. Road accident data analysis is a very important means to identify various factors associated with road accidents and can help in reducing the accident rate. In this study, we are making use of K-means clustering on a new road accident data from Alabama, America. The main focus to use these techniques is proving those identify technique and can perform better than other, retrieve all the information about road accident which classify on basis of attributes like   state, city, weather etc., This will be useful in reducing the road accidents.

Downloads

Download data is not yet available.