Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges

The computerized simulations of physical and socio-economic systems have proliferated in the past decade, at the same time, the capability to develop high-fidelity system predictive models is of growing importance for a multitude of reliability and system safety applications. Traditionally, methodol...

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Vydáno v:	Reliability engineering & system safety Ročník 230; s. 108900
Hlavní autoři:	Xu, Yanwen, Kohtz, Sara, Boakye, Jessica, Gardoni, Paolo, Wang, Pingfeng
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Barking Elsevier BV 01.02.2023
Témata:	Hybrid systems Learning algorithms Machine learning Modelling Motivation Physics Prediction models Reliability engineering Safety State-of-the-art reviews System effectiveness System reliability
ISSN:	0951-8320, 1879-0836
On-line přístup:	Získat plný text
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