Predicting shared-car use and examining nonlinear effects using gradient boosting regression trees-Reference-Cited by-同舟云学术

Predicting shared-car use and examining nonlinear effects using gradient boosting regression trees

Published:2020-10-05 Issue:12 Volume:15 Page:893-907
ISSN:1556-8318
Container-title:International Journal of Sustainable Transportation
language:en
Short-container-title:International Journal of Sustainable Transportation

Author:

Wang Tao¹^ORCID,Hu Songhua²^ORCID,Jiang Yuan³

Affiliation:

1. School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai, China

2. Department of Civil and Environmental Engineering, University of Maryland, College Park, MD, USA

3. Department of Planning, Chengdu Institute of Planning & Design, Chengdu, China

Publisher

Informa UK Limited

Subject

Transportation,Automotive Engineering,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Civil and Structural Engineering,Environmental Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/15568318.2020.1827316

Reference37 articles.

1. Comparing car-sharing schemes in Switzerland: User groups and usage patterns

2. Modeling free-floating car-sharing use in Switzerland: A spatial regression and conditional logit approach

3. Weak signals in the mobility landscape: car sharing in ten European cities

4. Classification And Regression Trees

5. Carpooling and carsharing for commuting in the Paris region: A comprehensive exploration of the individual and contextual correlates of their uses

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