Analysing Road Accident Fatal Data Using K-Means, DBSCAN and Farthest First Algorithms

Abstract

Road injuries are one of the most important factors impacting people's immediate deaths and raising the rates of economic development in both private and public property. Analysis of road accidents may provide information on the position of certain features that can be used to reduce accident risk. The heterogeneity of data relating to road accidents is a major challenge in study of road safety. In this study, Density Based Spatial clustering(DBSCAN) , clustering of k-means and Farthest First Algorithm which helps in analyzing the cause of the accident to identify the accuracy of fatal rate. Further, Apriori Association Rule Mining is applied on the clusters .After clustering the data using DBSCAN , clustering k-means and Farthest First Algorithm, the result gives the better accuracy of fatal rate.

Keywords: Apriori Algorithm, K-meanss, Density Based Spatial Clustering(DBSCAN), Farthest First Algorithm Road accident fatal analysis