Abstract: For Bayesian network structure learning with continuous data, traditional methods typically require data discretization or assume that the data follows a Gaussian distribution. However, the ...

You can obtain user guides for BN Modeller application with the following link https://digiratory.github.io/bayes_model/. It covers various aspects of using BN ...

This project implements a comprehensive Fuzzy Bayesian Network (FBN) system that combines fuzzy logic with probabilistic reasoning for advanced cybersecurity risk assessment. The system handles ...

Cross-sectional network analysis was employed to explore the complex relationships between depression, anxiety, insomnia, somatic symptoms, childhood trauma, self-esteem, social support, and emotional ...

Abstract: This study proposes a Dynamic Bayesian Network (DBN)-based model for evaluating the reliability of optical networks, effectively quantifying the state changes and reliability of optical ...

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 ...

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