Understanding drivers' route choice behaviours in the urban network with machine learning models-Reference-Cited by-同舟云学术

Understanding drivers' route choice behaviours in the urban network with machine learning models

Published:2018-09-28 Issue:3 Volume:13 Page:427-434
ISSN:1751-9578
Container-title:IET Intelligent Transport Systems
language:en
Short-container-title:IET Intelligent Transport Systems

Author:

Lai Xinjun¹^ORCID,Fu Hui²,Li Jun³,Sha Zhiren⁴

Affiliation:

1. Guangdong CIM Provincial Key LabSchool of Electro‐Mechanical Engineering Guangdong University of TechnologyRoom 615, Engineering Building No. 2, Waihuanxi Road 100, HEMCGuangzhou510006People's Republic of China

2. School of Electro‐Mechanical Engineering, Guangdong University of TechnologyRoom 618, Engineering Building No. 2, Waihuanxi Road 100, HEMCGuangzhou510006People's Republic of China

3. Guangdong ITS Provincial Key LabSchool of Intelligent Systems Engineering, Sun Yat‐Sen UniversityRoom A303, Engineering Building, Waihuandong Road 132, HEMCGuangzhou510006People's Republic of China

4. Guangdong Fundway Science and Technology Co., LtdFloor 8, Building A, Qinglan Street 22, HEMCGuangzhou510006People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Law,Mechanical Engineering,General Environmental Science,Transportation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-its.2018.5190

Reference34 articles.

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5. Consumer credit risk: Individual probability estimates using machine learning

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