|Communications on Applied Electronics
|Foundation of Computer Science (FCS), NY, USA
|Volume 6 - Number 4
|Year of Publication: 2016
|Authors: S. Vasavi
S. Vasavi . A Survey on Extracting Hidden Patterns within Road Accident Data using Machine Learning Techniques. Communications on Applied Electronics. 6, 4 ( Dec 2016), 1-6. DOI=10.5120/cae2016652455
Road Accidents may not be stopped altogether, but can be reduced. Driver emotions such as sad, happy, anger etc can be one reason for accidents. At the same time environment conditions such as weather, traffic on the road, load in the vehicle, type of road, health condition of driver, speed etc can also be the reasons for accidents. Hidden patterns in accidents can be extracted so as to find the common features between accidents. This paper presents the literature survey and the results of the framework from the research study on road accident data of major national highways that pass through Krishna district (18 stations) for the year 2013 by applying machine learning techniques into analysis. Results showed that the selected machine learning techniques are able to extract hidden patterns from the data. Density histograms are used for accident data visualization.