Probabilistic traffic breakdown forecasting through Bayesian approximation using variational LSTMs
Author:
Affiliation:
1. Department of Industrial and Transportation Engineering, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
Funder
CAPES
Publisher
Informa UK Limited
Subject
Transportation,Modeling and Simulation,Software
Link
https://www.tandfonline.com/doi/pdf/10.1080/21680566.2022.2164529
Reference43 articles.
1. A Review of Traffic Congestion Prediction Using Artificial Intelligence
2. Explaining and Interpreting LSTMs
3. Effect of Geometry and Control on the Probability of Breakdown and Capacity at Freeway Merges
4. Patient Subtyping via Time-Aware LSTM Networks
5. Reliability of Freeway Traffic Flow: A Stochastic Concept of Capacity;Brilon W.;Proceedings of the 16th International Symposium on Transportation and Traffic Theory,2005
Cited by 2 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. Exploring traffic breakdown with vehicle-level data;Journal of Intelligent Transportation Systems;2024-01-08
2. Prediction of Freeway Traffic Breakdown Using Artificial Neural Networks;Algorithms;2023-06-15
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