计算机应用研究2016，Vol.33Issue(3)：806-809,4.DOI:10.3969/j.issn.1001-3695.2016.03.037
基于灰色关联的 LS-SVM道路交通事故预测
Forecast model of road traffic accidents based on LS-SVMwith grey correlation analysis
戢小辉1
作者信息
- 1. 西南交通大学 交通运输与物流学院，成都 610031
- 折叠
摘要
Abstract
In order to improve the predicting accuracy and modeling speed of road traffic accidents,this paper proposed the LS-SVMroad traffic accidents forecast model with grey correlation analysis on the basis of analyzing the influencing factors of road traffic accidents.It screened the input variables of LS-SVMby grey correlation analysis to simplify the LS-SVMstructure, and applied the dynamic change inertia weight adaptive particle swarm optimization algorithm (DCW-APSO)to optimize selec-tion of model parameters.It also applied the model to forecast the integrated mortality rate of road traffic accidents from 1996 to 2000,and compared the results with other type of model.The comparison result shows that compared to other predictive models,the proposed model provides a better convergence rate and higher predicting accuracy.关键词
道路交通事故/预测/灰色关联分析/最小二乘支持向量机/动态改变惯性权重自适应粒子群算法Key words
road traffic accidents/forecast/grey correlation analysis/LS-SVM/DCW-APSO分类
信息技术与安全科学引用本文复制引用
戢小辉..基于灰色关联的 LS-SVM道路交通事故预测[J].计算机应用研究,2016,33(3):806-809,4.
