Abstract
The fatalities due to road traffic injuries have a great effect on society. The time of occurrence of road accidents can’t be predicted exactly but the reasons for road accident fatalities can be analyzed by a prediction model, so that care can be taken to reduce the risk. Several factors like age, gender, region, speed, etc., affect the occurrence of accidents on roads. Our paper presents a neural network model to predict the situations that could influence fatality rate in road accidents and identifies the factors that play a vital role in affecting the fatality rate. The work also addresses various solutions for class imbalance problem that arises in typical situations. Using the model, the relation between the attributes and fatality rate is analyzed.
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Rekha Sundari, M., Reddi, P., Satyanarayana Murthy, K., Sai Sowmya, D. (2023). Fatality Prediction in Road Accidents Using Neural Networks. In: Mahapatra, R.P., Peddoju, S.K., Roy, S., Parwekar, P. (eds) Proceedings of International Conference on Recent Trends in Computing. Lecture Notes in Networks and Systems, vol 600. Springer, Singapore. https://doi.org/10.1007/978-981-19-8825-7_3
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DOI: https://doi.org/10.1007/978-981-19-8825-7_3
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