A Comparative Study of Using Spatial-Temporal Graph Convolutional Networks for Predicting Availability in Bike Sharing Schemes-Reference-Cited by-同舟云学术

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A Comparative Study of Using Spatial-Temporal Graph Convolutional Networks for Predicting Availability in Bike Sharing Schemes

Published:2021-09-19 Issue: Volume: Page:
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Container-title:2021 IEEE International Intelligent Transportation Systems Conference (ITSC)
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Author:

Chen Zhengyong,Wu Hongde,O'Connor Noel E.,Liu Mingming

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9564393/9564395/09564831.pdf?arnumber=9564831

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Multi-Scale Residual Graph Convolution Network with hierarchical attention for predicting traffic flow in urban mobility;Complex & Intelligent Systems;2024-01-29

2. A Spatial-Temporal Graph Convolutional Recurrent Network for Transportation Flow Estimation;Sensors;2023-08-30

3. Global spatio‐temporal dynamic capturing network‐based traffic flow prediction;IET Intelligent Transport Systems;2023-05-22

4. A Survey on Graph Neural Networks for Microservice-Based Cloud Applications;Sensors;2022-12-05

5. Graph-PHPA: Graph-based Proactive Horizontal Pod Autoscaling for Microservices using LSTM-GNN;2022 IEEE 11th International Conference on Cloud Networking (CloudNet);2022-11-07

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