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	Hybrid artificial neural network and locally weighted regression models for lane-based short-term urban traffic flow forecasting
	Raza, Asif; Zhong, Ming*
刊名	Transportation Planning and Technology
	2018
卷号	41期号:8页码:901-917
关键词	Traffic flow aggregate model artificial neural network disaggregate model genetic algorithms locally weighted regression short-term forecasting
ISSN号	0308-1060
DOI	10.1080/03081060.2018.1526988
URL标识	查看原文
WOS记录号	WOS:000447230700006
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/3372993
专题	武汉理工大学
作者单位	[Zhong, Ming] Wuhan Univ Technol, Intelligent Transportat Syst Res Ctr, Engn Res Ctr Transportat Safety, POB 125,1040 Heping Ave, Wuhan 430063, Hubei, Peoples R China.
推荐引用方式 GB/T 7714	Raza, Asif,Zhong, Ming*. Hybrid artificial neural network and locally weighted regression models for lane-based short-term urban traffic flow forecasting[J]. Transportation Planning and Technology,2018,41(8):901-917.
APA	Raza, Asif,&Zhong, Ming*.(2018).Hybrid artificial neural network and locally weighted regression models for lane-based short-term urban traffic flow forecasting.Transportation Planning and Technology,41(8),901-917.
MLA	Raza, Asif,et al."Hybrid artificial neural network and locally weighted regression models for lane-based short-term urban traffic flow forecasting".Transportation Planning and Technology 41.8(2018):901-917.

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