Abstract: This study proposed a risk assessment method based on Bayesian networks for complex system engineering with multiple types of work, strong concealment, and multiple uncertain factors.

Abstract: Bayesian networks are widely used for causal discovery and probabilistic modeling across diverse domains including healthcare, multi-dimensional data analysis, environmental modeling, and ...

Investigators are hoping to find clues as to why the Bayesian superyacht sank off the coast of Sicily 10 months ago, killing seven people. By Emma Bubola and Jeffrey Gettleman The hull of the Bayesian ...

Bayesian methods for inference and prediction have become widespread in the social sciences (and beyond). Over the last decades, applied Bayesian modeling has evolved from a niche methodology with ...

Background: Ethno-racial disparities in cardiometabolic diseases are driven by socioeconomic, behavioral, and environmental factors. Bayesian networks offer an approach to analyze the complex ...

Relay protection rejection and misoperation exist in the existing distribution network, which will affect the fault diagnosis results. To diagnose faults in distribution networks, this paper presents ...

Bayesian networks, also known as Bayes nets, belief networks, or decision networks, are a powerful tool for understanding and reasoning about complex systems under uncertainty. They are essentially ...

In recent years, large-scale neural networks have ushered in a transformative era in generative modeling. These neural networks possess an unprecedented capacity to capture intricate relationships ...