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基于粒子群优化SVM的高速公路交通事件检测
引用本文:胡丹龙,余立建,杨阳.基于粒子群优化SVM的高速公路交通事件检测[J].交通科技与经济,2013(2):63-65.
作者姓名:胡丹龙  余立建  杨阳
作者单位:西南交通大学交通信息工程及控制实验室,四川成都610031
摘    要:为了更加准确地检测出高速公路上的偶发性交通事件,采用一种粒子群优化SVM参数的高速公路交通事件检测算法,提升事件检测效果。文中运用高速公路实测数据集(L880),对支持向量机算法进行分类性能测试,并且采用改进的粒子群优化算法对支持向量机的参数进行优化,进而利用测试集数据对该模型进行验证比较,获得满意的检测效果。

关 键 词:交通事件检测  支持向量机  I-880数据库  粒子群优化

SVM highway traffic incident detection based on particle swarm optimization
HU Dan-long,YU Li-jian,YANG Yang.SVM highway traffic incident detection based on particle swarm optimization[J].Technology & Economy in Areas of Communications,2013(2):63-65.
Authors:HU Dan-long  YU Li-jian  YANG Yang
Institution:(Traffic Information Engineering and Control Laboratory,Southwest J iaotong University,Chengdu (310031,China)
Abstract:In order to accurately detect the occasional highway traffic incident, a SVM parameter highway traffic incident detection algorithm is provided based on particle swarm optimization. The highway measured data set (I-880) is adopted and the support vector algorithm is tested for classification performance. The improved particle swarm optimization algorithm is used to optimize the parameters of support vector machine, and then the model under test is validated, resulting in the satisfactory effect.
Keywords:traffic incident detection  support vector machines  1-880 database  particle swarm optimization
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