An ISM-based virtual fault tree and a graph convolutional network are combined to predict Fussell-Vesely importance on two small nuclear subsystems, with claims of millisecond inference and high accuracy.
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A Hybrid Real-Time Framework for Efficient Fussell-Vesely Importance Evaluation Using Virtual Fault Trees and Graph Neural Networks
An ISM-based virtual fault tree and a graph convolutional network are combined to predict Fussell-Vesely importance on two small nuclear subsystems, with claims of millisecond inference and high accuracy.