Functional Zone Based Hierarchical Demand Prediction For Bike System Expansion

Author:

Liu Junming1,Sun Leilei2,Li Qiao1,Ming Jingci1,Liu Yanchi1,Xiong Hui1

Affiliation:

1. Rutgers University, Newark, NJ, USA

2. Tsinghua University, Beijing, China

Funder

National Natural Science Foundation of China

National Science Foundation

Publisher

ACM

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1. MulSTE: A Multi-view Spatio-temporal Learning Framework with Heterogeneous Event Fusion for Demand-supply Prediction;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

2. A new soft clustering method for traffic prediction in bike-sharing systems;International Journal of Sustainable Transportation;2024-06-03

3. Time-dependent trip generation for bike sharing planning: A multi-task memory-augmented graph neural network;Information Fusion;2024-06

4. An Adaptive Spatial-Temporal Method Capturing for Short-Term Bike-Sharing Prediction;IEEE Transactions on Intelligent Transportation Systems;2024

5. Equity-Aware Cross-Graph Interactive Reinforcement Learning for Bike Station Network Expansion;Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems;2023-11-13

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