Highway Traffic Accident Prediction Based on SVR Trained by Genetic Algorithm

被引:2
作者
Yang, Zhen-Qi [1 ]
机构
[1] Shandong Jiaotong Univ, Jinan 250023, Peoples R China
来源
MATERIALS SCIENCE AND INFORMATION TECHNOLOGY, PTS 1-8 | 2012年 / 433-440卷
关键词
Highway traffic accident; support vector regression; prediction model; genetic algorithm;
D O I
10.4028/www.scientific.net/AMR.433-440.5886
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The multi researches and experiments show that the future highway traffic accident situation is shown by the highway traffic accident prediction. In the paper, support vector regression trained by genetic algorithm is presented in highway traffic accident prediction. In the method, genetic algorithm is used to train the parameters of support vector regression. Firstly, the regression function of support vector regression algorithm is introduced, and the parameters of support vector regression are optimized by genetic algorithm. The computation results between G-SVR and SVR can indicate that the prediction ability for highway traffic accidents of G-SVR is better than that of SVR absolutely.
引用
收藏
页码:5886 / 5889
页数:4
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