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    Algorithms for Bayesian Network Modeling, Inference, and Reliability Assessment for Multistate Flow Networks 

    Source: Journal of Computing in Civil Engineering:;2017:;Volume ( 031 ):;issue: 005
    Author(s): Yanjie Tong; Iris Tien
    Publisher: American Society of Civil Engineers
    Abstract: The Bayesian network (BN) is a useful tool for the modeling and reliability assessment of civil infrastructure systems. For a system comprising many interconnected components, it captures the probabilistic dependencies ...
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    Probability Propagation Method for Reliability Assessment of Acyclic Directed Networks 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2019:;Volume ( 005 ):;issue: 003
    Author(s): Yanjie Tong; Iris Tien
    Publisher: American Society of Civil Engineers
    Abstract: Many civil infrastructure systems that deliver resources from source points to sinks, e.g., power distribution and gas pipeline networks, can be described as acyclic directed networks comprising nodes and links. ...
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    Time-Series Prediction in Nodal Networks Using Recurrent Neural Networks and a Pairwise-Gated Recurrent Unit Approach 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2022:;Volume ( 008 ):;issue: 002:;page 04022002
    Author(s): Yanjie Tong; Iris Tien
    Publisher: ASCE
    Abstract: Characteristics at nodes in a network, such as values of demand, evolve over time. To make time-dependent decisions for a network, making time series predictions at each node in the network over time is often necessary. ...
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