Prediction Model for Road Traffic Accident Based on Support Vector

Rong Cheng, Xiaoqiang Tian, Mengmeng Zhang


More than 1.3 million people worldwide die in road traffic accidents every year. With that in mind, traffic safety has become a top priority to the road traffic system development. Research in progress of road traffic accidents mainly from accidents numbers and the degree of accident damage. Firstly, this paper proposes a support vector prediction model for predicting the amount of road traffic accidents, which applied to the actual to verify the validity of the model by using the R software to solve it. Finally, it is found to the problem on a small scale has a better prediction effect which for the support vector model by comparing with the random forest model.


Traffic Accident; Prediction Model; Support Vector


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