Traffic Flow Prediction With Big Data: A Deep Learning Approach

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 平行智能技术与系统团队

	Traffic Flow Prediction With Big Data: A Deep Learning Approach
	Lv, Yisheng1 ; Duan, Yanjie1 ; Kang, Wenwen 1; Li, Zhengxi 2; Wang, Fei-Yue1
发表期刊	IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
	2015-04-01
卷号	16 期号:2 页码:865-873
文章类型	Article
摘要	Accurate and timely traffic flow information is important for the successful deployment of intelligent transportation systems. Over the last few years, traffic data have been exploding, and we have truly entered the era of big data for transportation. Existing traffic flow prediction methods mainly use shallow traffic prediction models and are still unsatisfying for many real-world applications. This situation inspires us to rethink the traffic flow prediction problem based on deep architecture models with big traffic data. In this paper, a novel deep-learning-based traffic flow prediction method is proposed, which considers the spatial and temporal correlations inherently. A stacked autoencoder model is used to learn generic traffic flow features, and it is trained in a greedy layerwise fashion. To the best of our knowledge, this is the first time that a deep architecture model is applied using autoencoders as building blocks to represent traffic flow features for prediction. Moreover, experiments demonstrate that the proposed method for traffic flow prediction has superior performance.
关键词	Deep Learning Stacked Autoencoders (Saes) Traffic Flow Prediction
WOS标题词	Science & Technology ; Technology
关键词[WOS]	NEURAL-NETWORK APPROACH ; MODELS ; MULTIVARIATE ; VOLUME ; REGRESSION ; ALGORITHM
收录类别	SCI
语种	英语
WOS研究方向	Engineering ; Transportation
WOS类目	Engineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology
WOS记录号	WOS:000352282500029
引用统计	被引频次：1932[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/8129
专题	多模态人工智能系统全国重点实验室_平行智能技术与系统团队
通讯作者	Lv, Yisheng
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.North China Univ Technol, Beijing 100144, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Lv, Yisheng,Duan, Yanjie,Kang, Wenwen,et al. Traffic Flow Prediction With Big Data: A Deep Learning Approach[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2015,16(2):865-873.
APA	Lv, Yisheng,Duan, Yanjie,Kang, Wenwen,Li, Zhengxi,&Wang, Fei-Yue.(2015).Traffic Flow Prediction With Big Data: A Deep Learning Approach.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,16(2),865-873.
MLA	Lv, Yisheng,et al."Traffic Flow Prediction With Big Data: A Deep Learning Approach".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 16.2(2015):865-873.

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