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Traffic congestion propagation inference using dynamic Bayesian graph convolution network
Transportation Research Part C: Emerging Technologies, 2022Ruimin Ke, Zhou Huang, Sen Luan
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Dynamic and Temporal Bayesian Networks
2015Dynamic Bayesian network models extend BNs to represent the temporal evolution of a certain process. There are two basic types of Bayesian network models for dynamic processes: state based and event based. Dynamic Bayesian networks are state-based models that represent the state of each variable at discrete time intervals.
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Dynamic Bayesian Network for Predicting Tunnel-Collapse Risk in the Case of Incomplete Data
Journal of Performance of Constructed Facilities, 2022Bo Wu, Jie Jiang, Jie Jiang
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A quantitative framework for network resilience evaluation using Dynamic Bayesian Network
Computer Communications, 2022Yuyang Zhou +2 more
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Dynamic availability assessment of safety critical systems using a dynamic Bayesian network
Reliability Engineering and System Safety, 2018Syed Imtiaz, Md Tanjin Amin
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A driver fatigue recognition model based on information fusion and dynamic Bayesian network
Information Sciences, 2010Guosheng Yang, Yingzi Lin
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Fault detection and pathway analysis using a dynamic Bayesian network
Chemical Engineering Science, 2019Syed Imtiaz, Md Tanjin Amin
exaly

