| 一种基于近似支撑矢量机(PSVM)的交通目标分类方法 |
| |
| 引用本文： | 王怡,王夏黎,周明全,李丙春.一种基于近似支撑矢量机(PSVM)的交通目标分类方法[J].计算机应用与软件,2005,22(12):112-114. |
| |
| 作者姓名： | 王怡 王夏黎 周明全 李丙春 |
| |
| 作者单位： | 西北大学计算机系可视化研究所,陕西,西安,710069;长安大学信息工程学院,陕西,西安,710064 |
| |
| 摘 要： | 本文介绍了支撑向量机的特点，给出了实际应用中传统支撑矢量机存在的问题。为了克服支撑矢量机算法的不足，引入了一种近似支撑矢量机（PSVM）算法，并将此算法用于交通目标的分类识别。实验结果表明此算法比BP神经网络法准确率高，比传统的SVM法的效率高。
|
| 关 键 词： | 支撑矢量机 近似支撑矢量机 交通目标 分类 神经网络 |
| 收稿时间： | 2005-02-22 |
| 修稿时间： | 2005-02-22 |
AN APPROACH FOR TRAFFIC OBJECT CLASSIFICATION BASED ON PROXIMAL SUPPORT VECTOR MACHINE |
| |
| Wang Yi,Wang Xiali,Zhou Mingquan,Li Bingchun.AN APPROACH FOR TRAFFIC OBJECT CLASSIFICATION BASED ON PROXIMAL SUPPORT VECTOR MACHINE[J].Computer Applications and Software,2005,22(12):112-114. |
| |
| Authors: | Wang Yi Wang Xiali Zhou Mingquan Li Bingchun |
| |
| Abstract: | The paper describes the traditional support vector machine(SVM) and some features of it,and discusses some problems in some applications.In order to overcome the defections of traditional SVM,an approach of proximal support vector machine(PSVM) is presented.While the approach is applied to traffic object classification,the results show that the approach of PSVM is more accurate than BP nerve network,and more efficient than traditional SVM. |
| |
| Keywords: | Support vector machine Proximal support vector machine Traffic object Classification Nerver network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
