Imagine a scenario where a team of doctors faces a perplexing medical puzzle. A patient shows a range of symptoms, each pointing to multiple possible diseases. How can they navigate this diagnostic ...
Abstract: The progression of nuclear power plant accident scenarios involves complex parameter uncertainties and partial signal unavailability, significantly impacting the accuracy of risk analysis ...
A representation of the cause-effect mechanism is needed to enable artificial intelligence to represent how the world works. Bayesian Networks (BNs) have proven to be an effective and versatile tool ...
Anomaly response in aerospace systems increasingly relies on multi-model analysis in digital twins to replicate the system’s behaviors and inform decisions. However, computer model calibration methods ...
BaNDyT (Bayesian Network analisis of molecular Dynamic simulation Trajectories): software package that implements the Bayesian Network Modeling specifically attuned to the MD simulation trajectories ...
Abstract: This study introduces a novel approach that integrates dynamic Bayesian network with attention based spatio-temporal graph convolutional network to forecast railway train delays, capturing ...
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