| 基于多尺度分析与神经网络的交通流预测 |
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| 引用本文： | 黄美灵,陆百川,谭伟. 基于多尺度分析与神经网络的交通流预测[J]. 重庆交通学院学报, 2010, 0(3) |
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| 作者姓名： | 黄美灵 陆百川 谭伟 |
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| 作者单位： | 重庆交通大学交通运输学院;交通运输部公路科学研究院北京新桥技术发展有限公司; |
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| 基金项目： | 交通运输部科技项目(2008-319-814-060) |
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| 摘 要： | 针对实际交通系统时变复杂和变化的不确定性所带来的交通流量随机因素影响大、非线性强、规律性不明显的特征;采用小波多尺度分解的方法,将含有综合信息的时间序列分解为多个分量特征不同的时间序列,然后采用神经网络对各个分量分别进行预测,最后用实测数据进行了验证分析。结果表明,基于多尺度分析与神经网络预测模型比单神经网络预测模型预测精度高,可用于交通流的实时动态预测。
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| 关 键 词： | 交通流预测 多尺度分析 神经网络 仿真 |
Traffic Flow Prediction Based on Multi-scale Analysis and Neural Network |
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| HUANG Mei-ling,,LU Bai-chuan,TAN Wei. Traffic Flow Prediction Based on Multi-scale Analysis and Neural Network[J]. Journal of Chongqing Jiaotong University, 2010, 0(3) |
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| Authors: | HUANG Mei-ling LU Bai-chuan TAN Wei |
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| Affiliation: | HUANG Mei-ling1,2,LU Bai-chuan1,TAN Wei1(1.School of Traffic & Transportation Engineering,Chongqing Jiaotong University,Chongqing 400074,China,2.Beijing Xinqiao Technology Development Co.Ltd,Research Institute of High way Ministry of Transport,Beijing 100101,China) |
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| Abstract: | Aiming at characteristics of nonlinearity,strong interference and no obvious regularity of traffic flow caused by the complexity and uncertainty of time variance in current traffic system,a new approach is proposed for traffic flow prediction.Firstly,the traffic flow sequence made of different frequencies is decomposed into low and high frequencies in the multi-resolution analysis and the trend components are restored according to the reconstructing principle of wavelet coefficients.Secondly,the artificial ... |
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| Keywords: | traffic flow prediction multi-scale analysis artificial neural network simulation |
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