| 基于K近邻非参数回归的短时交通流预测方法 |
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| 引用本文： | 张涛,陈先,谢美萍,张玥杰.基于K近邻非参数回归的短时交通流预测方法[J].系统工程理论与实践,2010,30(2):376-384. |
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| 作者姓名： | 张涛 陈先 谢美萍 张玥杰 |
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| 作者单位： | 1. 上海财经大学信息管理与工程学院,上海,200433
2. 复旦大学计算机科学与技术学院,上海市智能信息处理重点实验室,上海,200433 |
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| 基金项目： | 国家自然科学基金，上海市自然科学基金，上海财经大学"211工程"三期重点学科建设项目，上海市智能信息处理重点实验室开放课题 |
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| 摘 要： | 采用K近邻的非参数回归方法对短时交通流量进行了预测,考察了模型中关键因素对预测效果的影响.在4种不同状态向量和预测算法组合下的实验方法比较中,以相邻四个时间间隔的流量和占有率数据作为状态向量,并采用带权重的预测算法取得了良好的效果.将利用K值构造的预测区间用于特殊路况的预测中,得到了明显的改进效果.最后,对非参数回归和神经网络的方法进行了比较,结果表明了非参数回归预测方法的高精度和强移植性.
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| 关 键 词： | 短时交通流预测 非参数回归 $K$近邻 预测区间 状态向量 |
K-NN based nonparametric regression method for short-term traffic flow forecasting |
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| ZHANG Tao,CHEN Xian,XIE Mei-ping,ZHANG Yue-jie.K-NN based nonparametric regression method for short-term traffic flow forecasting[J].Systems Engineering —Theory & Practice,2010,30(2):376-384. |
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| Authors: | ZHANG Tao CHEN Xian XIE Mei-ping ZHANG Yue-jie |
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| Institution: | ZHANG Tao~1,CHEN Xian~1,XIE Mei-ping~1,ZHANG Yue-jie~2 (1.School of Information Management , Engineering,Shanghai University of Finance , Economics,Shanghai 200433,China,2.School of Computer Science,Shanghai Key Laboratory of Intelligent Information Processing,Fudan University,China) |
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| Abstract: | This paper used the K-NN based nonparametric regression to forecast the short term traffic flow,and analyzed the effect caused by key factors' settings in the model.Within four methods of different setting in traffic state vector and forecast technique,the one which defines traffic flow and occupancy rate in 4 time lags as state vector,and uses weight-added forecast technique has the better simulation results.This paper applied the prediction interval calculated by K to forecast during unconventional road c... |
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| Keywords: | short-term traffic flow forecasting nonparametric regression K nearest neighbor prediction interval state vector |
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