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Ebike Sharing vs. Bike Sharing: Demand Prediction Using Deep Neural Networks and Random Forests

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References

2011Real-time routing with OpenStreetMap data521 cited
2018Applying a random forest method approach to model travel mode choice behavior491 cited
2017A comparative study of machine learning classifiers for modeling travel mode choice423 cited
2020Prediction and behavioral analysis of travel mode choice: A comparison of machine learning and logit models406 cited
2014Spatio-temporal patterns of a Public Bicycle Sharing Program: the effect of weather and calendar events257 cited
2022Predicting the travel mode choice with interpretable machine learning techniques: A comparative study170 cited
2014Modeling Demand for Bikesharing Systems96 cited
2019Financial system modeling using deep neural networks (DNNs) for effective risk assessment and prediction94 cited
2019Bike-sharing or taxi? Modeling the choices of travel mode in Chicago using machine learning93 cited
2020Expanding a(n) (electric) bicycle-sharing system to a new city: Prediction of demand with spatial regression and random forests72 cited
2022Predictive and prescriptive performance of bike-sharing demand forecasts for inventory management65 cited
2023Multi-task supply-demand prediction and reliability analysis for docked bike-sharing systems via transformer-encoder-based neural processes58 cited
2015Mode Choice for School Trips54 cited
2022

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The identification of significant features towards travel mode choice and its prediction via optimised random forest classifier: An evaluation for active commuting behavior

36 cited

2021Impact of E-Bikes on Cycling in Hilly Areas: Participants’ Experience of Electrically-Assisted Cycling in a UK Study32 cited

2022Causal impacts of the COVID-19 pandemic on daily ridership of public bicycle sharing in Seoul30 cited

Cited by

2024Exploring the factors affecting bike sharing usage in developing countries: a case study on Chandigarh, India6 cited
2025How does Bike Absence Influence Mode Shifts Among Dockless Bike-Sharing Users? Evidence From Nanjing, China4 cited