Citation

Parveen F, Shaik R, Raheem S, Raju SSH. Int. J. Res. Eng. Sci. Manag. 2023; 6(5): 95-97.

Copyright

(Copyright © 2023, RESAIM Publishing)

DOI

unavailable

PMID

unavailable

Abstract

Road accident is most unwanted thing to happen to a road user, though they happen quite often. The most unfortunate thing is that we don't learn from our mistakes on road. Most of the road users are quite well aware of the general rules and safety measures while using roads but it is only the laxity on part of road users, which cause accidents and crashes. Main cause of accidents and crashes are due to human errors. The unbalance of traffic incident data has a great influence on the detection effect. Therefore, a traffic incident detection method based on factor analysis and weighted random forest (FA-WRF) is designed. We have used different Machine Learning Algorithms such as Random Forest algorithm, XG Boost algorithm, Linear Regression algorithm and Support Vector Machine algorithm to predict the severity rate of the accident whether it is slight or fatal or severe.

Language: en

Keywords

Logistic Regression; Random Forest; SVM; XG Boost algorithm