A machine learning approach to predicting bicycle demand during the COVID-19 pandemic-Reference-Cited by-同舟云学术

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A machine learning approach to predicting bicycle demand during the COVID-19 pandemic

Published:2023-09 Issue: Volume:100 Page:101276
ISSN:0739-8859
Container-title:Research in Transportation Economics
language:en
Short-container-title:Research in Transportation Economics

Author:

Baumanis Carolina^ORCID,Hall Jennifer^ORCID,Machemehl Randy^ORCID

Publisher

Elsevier BV

Subject

Economics, Econometrics and Finance (miscellaneous),Transportation

Reference33 articles.

1. Regionally-structured explanations behind area-level populism: An update to recent ecological analyses;Beecham;PLoS One,2020

2. When Pandemic Hits: Exercise Frequency and Subjective Well-Being During COVID-19 Pandemic;Brand;Frontiers in Psychology,2020

3. Modal share changes due to COVID-19: The case of budapest;Bucsky;Transportation Research Interdisciplinary Perspectives,2020

4. How did outdoor biking and walking change during COVID-19?: A case study of three U.S. Cities;Doubleday;PLoS One,2021

5. People For Bikes. (2021). How bicycling changed during A pandemic. https://www.peopleforbikes.org/news/how-bicycling-changed-during-a-pandemic.

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Demand forecasting of shared bicycles based on combined deep learning models;Physica A: Statistical Mechanics and its Applications;2024-02

2. Ebike Sharing vs. Bike Sharing: Demand Prediction Using Deep Neural Networks and Random Forests;Sustainability;2023-09-19

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