@article{ref1,
title="Mining road traffic accident data to improve safety on road-related factors for classification and prediction of accident severity",
journal="International research journal of engineering and technology",
year="2016",
author="Kashyap, Jaideep and Singh, Chandra Prakash",
volume="3",
number="10",
pages="221-226",
abstract="A Road Traffic Accident is very serious matter of life. The World Health Organization (WHO) reports that about 1.24 million people of the world die annually on the roads. The Institute for Health Metrics and Evaluation (IHME) estimated about 907,900, 1.3 million and 1.4 million deaths from road traffic injuries in 1990, 2010 and 2013, respectively. Uttar Pradesh in particular one of the state of India, experiences the highest rate of such accidents. Thus, methods to reduce accident severity are of great interest to traffic agencies and the public at large. In this paper, we applied data mining technologies to link recorded road characteristics to accident severity and developed a set of rules that could be used by the Indian Traffic Agency to improve safety and could help to save precious life.    Key Words: Traffic Accident, Data Mining, Naïve Bayes, Classification, Prediction.<p /> <p>Language: en</p>",
language="en",
issn="2395-0072",
doi="",
url="http://dx.doi.org/"
}