基于粒子群优化SVM的高速公路交通事件检测

SVM highway traffic incident detection based on particle swarm optimization

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(I-880),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。

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.