Results 81 to 90 of about 5,779 (161)

Excess demand prediction for bike sharing systems. [PDF]

PLoS One, 2021
Liu X, Pelechrinis K.
europepmc   +1 more source

Features that influence bike sharing demand. [PDF]

Heliyon
Cortez-Ordoñez A, Vázquez PP, Sanchez-Espigares JA.   +2 more
europepmc   +1 more source

A long-term perspective on the COVID-19: The bike sharing system resilience under the epidemic environment. [PDF]

J Transp Health, 2022
Bi H, Ye Z, Zhang Y, Zhu H.
europepmc   +1 more source

Spatiotemporal variability and prediction of e-bike battery levels in bike-sharing systems. [PDF]

Sci Rep
Bassolas A, Grau-Escolano J, Vicens J.
europepmc   +1 more source

A new RNN based machine learning model to forecast COVID-19 incidence, enhanced by the use of mobility data from the bike-sharing service in Madrid. [PDF]

Heliyon, 2023
Muñoz-Organero M, Callejo P, Hombrados-Herrera MÁ.   +2 more
europepmc   +1 more source

Quantifying and Forecasting Emission Reductions in Urban Mobility: An IoT-Driven Bike-Sharing Analysis. [PDF]

Sensors (Basel)
Uche-Soria M, Tabuenca B, Halcón-Gibert G, Núñez-Guerrero Y.   +3 more
europepmc   +1 more source

Travel patterns of free-floating e-bike-sharing users before and during COVID-19 pandemic. [PDF]

Cities, 2023
Choi SE, Kim J, Seo D.
europepmc   +1 more source

Optimizing urban bike-sharing systems: a stochastic mathematical model for infrastructure planning. [PDF]

Cent Eur J Oper Res
Ahmadi SA, Ghasemi P, Ehmke JF.
europepmc   +1 more source

Understanding Bike-sharing Mobility Patterns in Response to the COVID-19 Pandemic

, 2022
jia j, Liu C, Zhang H, Xiao Y, Wang X.
europepmc   +1 more source

A bike-sharing demand prediction model based on Spatio-Temporal Graph Convolutional Networks. [PDF]

PeerJ Comput Sci
Zhou C, Hu J, Zhang X, Li Z, Yang K.
europepmc   +1 more source