Classifying types of victims in a traffic accident using machine learning methods

被引：0
|
作者：
Chang, Xuning [1 ]
Cai, Jiahui [2 ]
Fu, Hongxin [3 ]
Zhang, Zuoyu [4 ]
机构：
[1] Concord Coll, Shrewsbury SY5 7PF, Salop, England
[2] Han Acad, Hong Kong 000000, Peoples R China
[3] Miami Univ, Oxford, OH 45056 USA
[4] Univ Waterloo, Waterloo, ON N2L 3G1, Canada
来源：
INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, VIRTUAL REALITY, AND VISUALIZATION (AIVRV 2021) | 2021年 / 12153卷
关键词：
decision trees; neural network; traffic accident;
D O I：
10.1117/12.2626786
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
With many previous works being done in the field of analyzing traffic accidents using machine learning, classification of victims and their sex seems to be a missing field. We aim to train a model to classify the types of victims and their sex in a traffic accident using various classification models and a dataset containing traffic accident data in France in 2019. We experimented with the variables involved using ablation study and gave the factors that are most relevant in determining the types of victims.
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页数：7
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