Algorithms, Volume 13, Issue 3 (March 2020) – 25 articles
Cover Story (view full-size image): Dynamic Bayesian networks capture time-based causal relationships within their model nodes. When representing complex engineering systems, which are comprised of tightly integrated hardware, software, and human components, these connections support inferences about system-level diagnostics and prognostics that would otherwise be difficult to identify. New information received from sensors and other monitoring tools is used as evidence to update previous system health assessments. These models can be used to prepare system operators for rare-event accident scenarios, where an up-to-date understanding of a system’s health is critical for maintaining its current and future functionality. View this paper
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