Predicting station level demand in a bike‐sharing system using recurrent neural networks-Reference-Cited by-同舟云学术

Predicting station level demand in a bike‐sharing system using recurrent neural networks

Published:2020-03-27 Issue:6 Volume:14 Page:554-561
ISSN:1751-9578
Container-title:IET Intelligent Transport Systems
language:en
Short-container-title:IET Intelligent Transport Systems

Author:

Chen Po‐Chuan¹,Hsieh He‐Yen¹²,Su Kuan‐Wu¹,Sigalingging Xanno Kharis¹,Chen Yan‐Ru¹,Leu Jenq‐Shiou¹

Affiliation:

1. Department of Electronic and Computer EngineeringNational Taiwan University of Science and TechnologyTaipei City10607Taiwan

2. Institute of Information Science, Academia Sinica128 NankangTaipeiTaiwan

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.2019.0007

Reference41 articles.

1. LarsenJ.: ‘Bike‐sharing programs hit the streets in over 500 cities worldwide’. Available athttp://www.earth‐policy.org/plan_b_updates/2013/update112 accessed 25 April 2013

2. 2011 United Nations Department of Economic and Social Affairs P. Midgley Bicycle‐sharing schemes: enhancing sustainable mobility in urban areas 1 12

3. Citi Bike. New York City Bike Sharing System Data. Available athttps://www.citibikenyc.com/system‐data

4. Large-Scale Vehicle Sharing Systems: Analysis of Vélib'

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