Bike sharing usage prediction with deep learning: a survey

W Jiang - Neural Computing and Applications, 2022 - Springer
As a representative of shared mobility, bike sharing has become a green and convenient
way to travel in cities in recent years. Bike usage prediction becomes more important for …

Improving short-term bike sharing demand forecast through an irregular convolutional neural network

X Li, Y Xu, X Zhang, W Shi, Y Yue, Q Li - Transportation research part C …, 2023 - Elsevier
As an important task for the management of bike sharing systems, accurate forecast of travel
demand could facilitate dispatch and relocation of bicycles to improve user satisfaction. In …

Multi-task supply-demand prediction and reliability analysis for docked bike-sharing systems via transformer-encoder-based neural processes

M Xu, Y Di, H Yang, X Chen, Z Zhu - Transportation Research Part C …, 2023 - Elsevier
With the rise of sharing economy, bike-sharing systems (BSSs) have gained heated
attention, and their operations require accurate prediction of bike usage. Although many …

Developing a supervised learning-based simulation method as a decision support tool for rebalancing problems in bike-sharing systems

A Maleki, E Nejati, A Aghsami, F Jolai - Expert Systems with Applications, 2023 - Elsevier
Abstract Bike-Sharing Systems (BSSs) have exploded in popularity worldwide because of
their beneficial impacts on traffic, pollution levels, and public health, which has resulted in …

Forecasting bike sharing demand using quantum Bayesian network

R Harikrishnakumar, S Nannapaneni - Expert Systems with Applications, 2023 - Elsevier
In recent years, bike-sharing systems (BSS) are being widely established in urban cities to
provide a sustainable mode of transport, by fulfilling the mobility requirements of public …

[HTML][HTML] A column generation heuristic for the dynamic bicycle rebalancing problem

MD Gleditsch, K Hagen, H Andersson… - European Journal of …, 2022 - Elsevier
Public bicycle sharing systems are becoming an essential part of the future urban mobility
system. Real-time monitoring of the system state through sensors on bicycles and/or stations …

Enhancing multistep-ahead bike-sharing demand prediction with a two-stage online learning-based time-series model: insight from Seoul

S Leem, J Oh, J Moon, M Kim, S Rho - The Journal of Supercomputing, 2024 - Springer
Bike-sharing is a powerful solution to urban challenges (eg, expanding bike communities,
lowering transportation costs, alleviating traffic congestion, reducing emissions, and …

Bicycle sharing station planning: From free-floating to geo-fencing

Y Cai, GP Ong, Q Meng - Transportation research part C: emerging …, 2023 - Elsevier
Bicycle sharing systems (BSSs) are expanding with unparalleled speed all over the world
due to various advantages of cycling such as cost effectiveness, environmentally …

Modeling censored mobility demand through censored quantile regression neural networks

FB Hüttel, I Peled, F Rodrigues… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Shared mobility services require accurate demand models for effective service planning. On
the one hand, modeling the full probability distribution of demand is advantageous because …

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

M Schnieder - Sustainability, 2023 - mdpi.com
Background: Conventional bike sharing systems are frequently adding electric bicycles. A
major question now arises: Does the bike sharing system have a sufficient number of ebikes …