Mining spatio-temporal patterns of congested traffic in urban areas from traffic sensor data-Reference-Cited by-同舟云学术

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Mining spatio-temporal patterns of congested traffic in urban areas from traffic sensor data

Published:2016-11 Issue: Volume: Page:
ISSN:
Container-title:2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)
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Author:

Inoue Ryo,Miyashita Akihisa,Sugita Masatoshi

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/7784515/7795515/07795635.pdf?arnumber=7795635

Cited by 14 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. Interpretable Cascading Mixture-of-Experts for Urban Traffic Congestion Prediction;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

2. Urban Road Traffic Spatiotemporal State Estimation Based on Multivariate Phase Space–LSTM Prediction;Applied Sciences;2023-11-06

3. Land Use Impacts on Traffic Congestion Patterns: A Tale of a Northwestern Chinese City;Land;2022-12-14

4. Motorway Bottleneck Probability Estimation in Connected Vehicles Environment Using Speed Transition Matrices;Sensors;2022-04-06

5. Learning Congestion Propagation Behaviors for Traffic Prediction;2021 IEEE International Intelligent Transportation Systems Conference (ITSC);2021-09-19

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