| 基于最小二乘支持向量机的车型识别算法研究 |
| |
| 引用本文： | 李文勇,陶汉卿.基于最小二乘支持向量机的车型识别算法研究[J].公路交通科技,2010,27(1). |
| |
| 作者姓名： | 李文勇 陶汉卿 |
| |
| 作者单位： | 1. 桂林电子科技大学,机电工程学院,广西,桂林,541004;东南大学,交通学院,江苏,南京,210096
2. 东南大学,交通学院,江苏,南京,210096 |
| |
| 基金项目： | 国家自然科学基金资助项目(50808050);;广西科学研究与技术开发计划资助项目(0719001-2) |
| |
| 摘 要： | 以感应线圈车辆检测器检测数据为分析基础,给出了基于Bayes理论的感应曲线自适应特征提取流程和方法,对选取的12个统计特征指标进行提取和优选。选择了曲线宽度、最大值、波峰数量、最小波谷值和波谷比组成车型识别模型的特征输入向量,不仅降低了输入向量的维数,缩短了最小二乘支持向量机的训练时间,同时也可加快车型识别的分类速度,增强特征值的分类辨别能力,提高车型分类的可靠性。在提出的基于最小二乘支持向量机的车型识别算法中,采用了修剪算法,加快了计算速度,同时保持了良好的回归性能。通过实例分析证明:基于最小二乘支持向量机的车型识别算法可提高自学习能力和识别准确率。
|
| 关 键 词： | 智能运输系统 车型识别 最小二乘支持向量机 感应线圈 修剪算法 |
Study on Vehicle Type Identification Algorithm Based on Least Squares Support Vector Machine |
| |
| LI Wenyong,TAO Hanqing.Study on Vehicle Type Identification Algorithm Based on Least Squares Support Vector Machine[J].Journal of Highway and Transportation Research and Development,2010,27(1). |
| |
| Authors: | LI Wenyong TAO Hanqing |
| |
| Institution: | 1.School of Mechanical & Electrical Engineering;Guilin University of electronic Technology;Guilin Guangxi 541004;China;2.School of Transportation;Southeast University;Nanjing Jiangsu 210096;China |
| |
| Abstract: | On the basis of data from inductive coil,the induction curve adaptive characteristic pick-up process and method based on Bayes theory were presented.After picking-up and optimizing 12 selected statistic characteristics according to the method,curve width,maximum value,wave crest number,least trough value and trough ratio were chosen to constitute the characteristic input vectors of vehicle type identification model.This could not only reduce the dimensions of input vectors and cut the training time of least... |
| |
| Keywords: | Intelligent Transport Systems vehicle type identification LS-SVM inductive coil pruning algorithm |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
|
