A knowledge learning and random pruning-based memetic algorithm for user route planning in bike-sharing system
Author:
Funder
National Key Research and Development Program of China
Publisher
Springer Science and Business Media LLC
Subject
Control and Optimization,General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s12293-023-00389-w.pdf
Reference70 articles.
1. Wang W, Zhao X, Gong Z et al (2021) An attention-based deep learning framework for trip destination prediction of sharing bike. IEEE Trans Intell Transp Syst 22:4601–4610. https://doi.org/10.1109/TITS.2020.3008935
2. Jiménez P, Nogal M, Caulfield B, Pilla F (2016) Perceptually important points of mobility patterns to characterise bike sharing systems: the Dublin case. J Transp Geogr 54:228–239. https://doi.org/10.1016/j.jtrangeo.2016.06.010
3. Yan S, Lin JR, Chen YC, Xie FR (2017) Rental bike location and allocation under stochastic demands. Comput Ind Eng 107:1–11. https://doi.org/10.1016/j.cie.2017.02.018
4. Maas S, Attard M, Caruana MA (2020) Assessing spatial and social dimensions of shared bicycle use in a Southern European island context: the case of Las Palmas de Gran Canaria. Transp Res Part A Policy Pract 140:81–97. https://doi.org/10.1016/j.tra.2020.08.003
5. Li Y, Zheng Y (2020) Citywide bike usage prediction in a bike-sharing system. IEEE Trans Knowl Data Eng 32:1079–1091. https://doi.org/10.1109/TKDE.2019.2898831
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