基于自适应秩动态张量分析的短时交通流预测

doi:10.11959/j.issn.2096-3750.2019.00116

Abstract

Abstract:

Short-term traffic flow prediction in intelligent transportation system can provide data support in areas such as route planning,traffic management,public safety and so on.In order to improve the prediction accuracy with missing and abnormal data,a short-term traffic flow prediction method based on the adaptive rank dynamic tensor analysis was proposed.Firstly,a four dimensional tensor consisted of week,day,time and space was constructed,which could excavate the multimodal correlation of traffic flow data.Secondly,tensor flow data with dynamic structure was formed by using sliding window model.The principal component analysis (PCA) algorithm was extended to an offline tensor analysis algorithm that could accept tensor input.Then the adaptive rank and the forgetting factor were introduced to generate an adaptive rank dynamic tensor analysis algorithm.Finally,the tensor stream data was inputted into the adaptive rank dynamic tensor analysis algorithm to realize the short-term traffic flow prediction.The experimental results show that a good prediction can be achieved even with data missing.

Key words: short-term traffic flow prediction, data missing, dynamic tensor analysis, multimodal information

CLC Number:

TN915

Lingchao HE,Dong LIN,Xinxin FENG. Short-term traffic flow prediction based on adaptive rank dynamic tensor analysis[J]. Chinese Journal on Internet of Things, 2019, 3(3): 18-25.

Figures/Tables 8

References 23

[1]	张彦, 张科, 曹佳钰 ,等. 边缘智能驱动的车联网[J]. 物联网学报, 2018,2(4): 40-48.
	ZHANG Y , ZHANG K , CAO J Y ,et al. Internet of vehicles empowered by edge intelligence[J]. Chinese Journal on Internet of Things, 2018,2(4): 40-48.
[2]	余辰, 张丽娟, 金海 . 大数据驱动的智能交通系统研究进展与趋势[J]. 物联网学报, 2018,2(1): 56-63.
	YU C , ZHANG L J , JIN H . Research progress and trend of big data-driven intelligent transportation system[J]. Chinese Journal on Internet of Things, 2018,2(1): 56-63.
[3]	熊建芳 . 浅谈物联网在智能交通中的应用[J]. 智能计算机与应用, 2018,8(6): 177-179.
	XIONG J F . The application of the Internet of things in the intelligent transportation[J]. Intelligent Computer and Applications, 2018,8(6): 177-179.
[4]	ZHANG J , WANG F Y , WANG K ,et al. Data-driven intelligent transportation systems:a survey[J]. IEEE Transactions on Intelligent Transportation Systems, 2011,12(4): 1624-1639.
[5]	RAN B , JIN P J , BOYCE D ,et al. Perspectives on future transportation research:impact of intelligent transportation system technologies on next generation transportation modeling[J]. Journal of Intelligent Transportation Systems, 2012,16(4): 226-242.
[6]	CHEN Y , HU J , ZHANG Y ,et al. Traffic data analysis using kernel PCA and self-organizing map[C]// Intelligent Vehicles Symposium. IEEE, 2006.
[7]	QU L , ZHANG Y , HU J ,et al. A BPCA based missing value imputing method for traffic flow volume data[C]// Intelligent Vehicles Symposium. IEEE, 2008.
[8]	ZHANG Y , LIU Y . Missing traffic flow data prediction using least squares support vector machines in urban arterial streets[C]// 2009 IEEE Symposium on Computational Intelligence and Data Mining. IEEE, 2009: 76-83.
[9]	TAN H , FENG G , FENG J ,et al. A tensor-based method for missing traffic data completion[J]. Transportation Research Part C:Emerging Technologies, 2013,28: 15-27.
[10]	LIU J , MUSIALSKI P , WONKA P ,et al. Tensor completion for estimating missing values in visual data[J]. IEEE transactions on pattern analysis and machine intelligence, 2012,35(1): 208-220.
[11]	TOMIOKA R , HAYASHI K , KASHIMA H . On the extension of trace norm to tensors[C]// NIPS Workshop on Tensors,Kernels,and Machine Learning. 2010:7.
[12]	SIGNORETTO M , DE LATHAUWER L , SUYKENS J A K . Nuclear norms for tensors and their use for convex multilinear estimation[J].,2010:43. Submitted to Linear Algebra and Its Applications, 2010:43.
[13]	SIGNORETTO M , DINH Q T , DE LATHAUWER L ,et al. Learning with tensors:a framework based on convex optimization and spectral regularization[J]. Machine Learning, 2014,94(3): 303-351.
[14]	SHAN H , BANERJEE A , NATARAJAN R . Probabilistic tensor factorization for tensor completion[J]. Department of Computer Science and Engineering , 2011: 1-4.
[15]	ACAR E , DUNLAVY D M , KOLDA T G ,et al. Scalable tensor factorizations for incomplete data[J]. Chemometrics and Intelligent Laboratory Systems, 2011,106(1): 41-56.
[16]	SUN J , TAO D , FALOUTSOS C . Beyond streams and graphs:dynamic tensor analysis[C]// Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 2006: 374-383.
[17]	HAO F , JIAO M , MIN G ,et al. A trajectory-based recruitment strategy of social sensors for participatory sensing[J]. IEEE Communications Magazine, 2014,52(12): 41-47.
[18]	TAN H , WU Y , SHEN B ,et al. Short-term traffic prediction based on dynamic tensor completion[J]. IEEE Transactions on Intelligent Transportation Systems, 2016,17(8): 2123-2133.
[19]	DE LATHAUWER L , DE MOOR B , VANDEWALLE J . A multilinear singular value decomposition[J]. SIAM Journal on Matrix Analysis and Applications, 2000,21(4): 1253-1278.
[20]	MIN W , WYNTER L . Real-time road traffic prediction with spatio-temporal correlations[J]. Transportation Research Part C:Emerging Technologies, 2011,19(4): 606-616.
[21]	BRIN S , PAGE L . The anatomy of a large-scale hypertextual web search engine[J]. Computer Networks and ISDN Systems, 1998,30(1-7): 107-117.
[22]	LIU J , MUSIALSKI P , WONKA P ,et al. Tensor completion for estimating missing values in visual data[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012,35(1): 208-220.
[23]	CHEN X , HE Z , WANG J . Spatial-temporal traffic speed patterns discovery and incomplete data recovery via SVD-combined tensor decomposition[J]. Transportation Research Part C:Emerging Technologies, 2018,86: 59-77.

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算法	MAPE	MAE
四阶自适应秩动态张量分析	0.082	23.25
四阶动态张量分析	0.084	26.79
三阶动态张量分析	0.175	63.01
HaLRTC	0.269	90.78
Tucker-als	0.298	103.2

Short-term traffic flow prediction based on adaptive rank dynamic tensor analysis

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