ACCIDENT SEVERITY CLASSIFICATION USING MACHINE LEARNING.
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Automobiles are one of the greatest inventions of all times. They have simplified our lives and provided us withtremendous comfort. But there are two sides to every coin. They are one of the major causes of deaths in many countries. Driving while drowsy is a major cause for accidents in India and elsewhere. In India, more than 150,000 people are killed each year in traffic accidents, which is about 400 fatalities a day and far higher than developed countries like the US, which in 2016 logged about 40,000. In fact, as many as one third of fatal car accidents are linked to drowsy driving. In order to reduce these negative effects, it is important that measures be made on the scientific and objective front of the causes of accidents and severity of injuries. This project summarizes the performance of four machine learning paradigms applied to modelling the severity of injury that occurred during traffic accidents.
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[Kriti Dwivedi, Ajay Singh and Madhav Bharadwaj. (2019); ACCIDENT SEVERITY CLASSIFICATION USING MACHINE LEARNING. Int. J. of Adv. Res. 7 (Aug). 902-909] (ISSN 2320-5407). www.journalijar.com
Motilal Nehru National Institute of Technology
