Applying Bayesian spatio-temporal models to demand analysis of shared bicycle
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DOI: 10.1016/j.physa.2021.126296
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Cited by:
- Ma, Changxi & Liu, Tao, 2024. "Demand forecasting of shared bicycles based on combined deep learning models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
- Miqi Guo & Chaodong Gou & Shucheng Tan & Churan Feng & Fei Zhao, 2024. "Spatiotemporal Characteristics and Factors Influencing the Cycling Behavior of Shared Electric Bike Use in Urban Plateau Regions," Sustainability, MDPI, vol. 16(15), pages 1-18, July.
- Hua, Mingzhuang & Chen, Xuewu & Chen, Jingxu & Huang, Di & Cheng, Long, 2022. "Large-scale dockless bike sharing repositioning considering future usage and workload balance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
- Ma, Changxi & Zhao, Mingxi, 2023. "Spatio-temporal multi-graph convolutional network based on wavelet analysis for vehicle speed prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
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Keywords
Integrated Nested Laplace Approximation; Shared bicycle; Temporal and spatial correlation;All these keywords.
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