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	LSTM network: a deep learning approach for short-term traffic forecast
	Zhao, Zheng; Chen, Weihai; Wu, Xingming; Chen, Peter C.V.; Liu, Jingmeng
刊名	IET INTELLIGENT TRANSPORT SYSTEMS
	2017
卷号	11页码:68-75
关键词	learning (artificial intelligence) intelligent transportation systems road traffic control recurrent neural nets LSTM network LSTM deep-learning approach short-term traffic forecasting intelligent transportation system travel modes travel routes departure time traffic management traffic data analysis computation power long-short-term memory network temporal-spatial correlation two-dimensional network memory units
ISSN号	1751-956X
DOI	10.1049/iet-its.2016.0208
URL标识	查看原文
收录类别	SCIE ; EI
WOS记录号	WOS:000394500300061
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/5941139
专题	北京航空航天大学
推荐引用方式 GB/T 7714	Zhao, Zheng,Chen, Weihai,Wu, Xingming,et al. LSTM network: a deep learning approach for short-term traffic forecast[J]. IET INTELLIGENT TRANSPORT SYSTEMS,2017,11:68-75.
APA	Zhao, Zheng,Chen, Weihai,Wu, Xingming,Chen, Peter C.V.,&Liu, Jingmeng.(2017).LSTM network: a deep learning approach for short-term traffic forecast.IET INTELLIGENT TRANSPORT SYSTEMS,11,68-75.
MLA	Zhao, Zheng,et al."LSTM network: a deep learning approach for short-term traffic forecast".IET INTELLIGENT TRANSPORT SYSTEMS 11(2017):68-75.

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