| 一种在线快速判定交通流混沌的方法 |
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| 引用本文： | 张勇,贺国光.一种在线快速判定交通流混沌的方法[J].长沙交通学院学报,2007,23(2):36-40. |
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| 作者姓名： | 张勇 贺国光 |
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| 作者单位： | 天津大学,管理学院,天津,300072 |
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| 摘 要： | 对混沌、非混沌交通流序列进行了多尺度分解,发现在高频系数部分存在明显结构上的差异,依据这种差异提出了一种基于系统历史信息的在线快速判定交通流混沌的方法.实验结果表明:新的混沌判定方法比传统的混沌判定方法需要的样本数少、识别率高.该判定方法同样适用于其他确定系统在线混沌现象的快速判定.
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| 关 键 词： | 混沌 多尺度分解 高频系数 支持向量机 混沌判定 交通流 特征模式 |
| 文章编号： | 1000-9779（2007）02-0036-05 |
| 收稿时间： | 2006-10-30 |
| 修稿时间： | 2006-10-30 |
A method of on-line fast identification for the chaos in traffic flow |
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| ZHANG Yong,HE Guo-guang.A method of on-line fast identification for the chaos in traffic flow[J].Journal of Changsha Communications University,2007,23(2):36-40. |
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| Authors: | ZHANG Yong HE Guo-guang |
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| Institution: | College of Management, Tianjin University, Tianjin 300072, China |
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| Abstract: | The chaos and non-chaos traffic flow are multi-scale decomposed,the results indicate that different category sequence have different structure in high frequency coefficient.Using this difference one method of identification for the chaos traffic flow based history information is put forward.The experimental result indicates that the new identification method can use fewer samples than traditional method and the recognition rate is high.This method is also suitable for identification for chaos of other definite system. |
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| Keywords: | chaos multi-scale decompose high frequency coefficient support vector machine chaos identification traffic flow characteristic pattern |
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