| 数据挖掘在中观交通仿真器模型研究中的应用 |
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| 引用本文： | 江竹,赵飞,符杰.数据挖掘在中观交通仿真器模型研究中的应用[J].北京理工大学学报,2012(S1):174-178. |
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| 作者姓名： | 江竹 赵飞 符杰 |
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| 作者单位： | 西华大学能源与环境学院, 四川, 成都 610039;西华大学人事处, 四川, 成都 610039;西华大学能源与环境学院, 四川, 成都 610039 |
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| 基金项目： | 国家教育部省部共建重点实验室资助(SBZDPY-11-5,SBZDPY-11-4);西华大学重点科研基金资助项目(Z1120413);四川省教育厅重点资助项目(11ZA009) |
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| 摘 要： | 为克服经典速度-密度模型刻画道路交通流动态变化特性的缺陷,将更丰富的路段检测信息运用到中观交通仿真模型参数的标定过程中. 提出先对路段检测器数据进行预处理,再采用数据挖掘中的局部加权回归,K-Means,k-最近邻以及凝聚层次聚类算法,分别将车流密度、密度与流量作为变量标定车速. 利用现场数据对算法进行了大量测试,结果表明算法是有效的,适用于基于仿真的动态交通分配系统.
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| 关 键 词： | 中观交通仿真 速度-密度模型 标定 数据挖掘 |
| 收稿时间： | 2012/9/28 0:00:00 |
Application of Data Mining in Mesoscopic Traffic Simulator Modeling |
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| JIANG Zhu,ZHAO Fei and FU Jie.Application of Data Mining in Mesoscopic Traffic Simulator Modeling[J].Journal of Beijing Institute of Technology(Natural Science Edition),2012(S1):174-178. |
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| Authors: | JIANG Zhu ZHAO Fei and FU Jie |
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| Institution: | School of Energy and Environment, Xihua University, Chengdu, Sichuan 610039, China;The Personal Department, Xihua University, Chengdu, Sichuan 610039, China;School of Energy and Environment, Xihua University, Chengdu, Sichuan 610039, China |
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| Abstract: | In order to solve the limitation that the classical speed-density model describes the dynamic change characteristics of the traffic flow, more road detected information is utilized in the process of the parameters calibration of the model in the mesoscopic traffic simulator. Firstly, the detector data were preprocessed, and then, the data mining, including locally weighted regression, K-Means clustering and k-nearest neighborhood and agglomerative hierarchical cluster, was used to calibrate vehicle speed, vehicle density as well as densities and flows. The test with field data shows that the proposed algorithms have great performance in the parameters estimation for DTA based simulation. |
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| Keywords: | mesoscopic traffic simulation speed-density model calibration data mining |
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