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Traffic Flow Prediction With Big Data: A Deep Learning Approach
文献类型：期刊论文
| 作者 | Lv, Yisheng1 ; Duan, Yanjie1; Kang, Wenwen1; Li, Zhengxi2; Wang, Fei-Yue1
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| 刊名 | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
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| 出版日期 | 2015-04-01 |
| 卷号 | 16期号:2页码:865-873 |
| 关键词 | Deep learning stacked autoencoders (SAEs) traffic flow prediction |
| 通讯作者 | Lv, Yisheng |
| 英文摘要 | 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. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Engineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology |
| 研究领域[WOS] | Engineering ; Transportation |
| 关键词[WOS] | NEURAL-NETWORK APPROACH ; MODELS ; MULTIVARIATE ; VOLUME ; REGRESSION ; ALGORITHM |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000352282500029 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/8129]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队 |
| 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 |
| 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. |
入库方式： OAI收割
来源：自动化研究所
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