The design of Bayesian diagnostic expert system Querix and it’s engineering application

0578435 - ÚT 2024 CZ eng C - Konferenční příspěvek (zahraniční konf.)
Věchet, Stanislav - Krejsa, Jiří - Chen, K.-S.
The design of Bayesian diagnostic expert system Querix and it’s engineering application.
Engineering Mechanics 2023. Prague: Institute of Thermomechanics of the Czech Academy of Sciences, 2023 - (Radolf, V.; Zolotarev, I.), s. 259-262. ISBN 978-80-87012-84-0. ISSN 1805-8248. E-ISSN 1805-8256.
[Engineering Mechanics 2023 /29./. Milovy (CZ), 09.05.2023-11.05.2023]
Grant ostatní: AV ČR(CZ) MOST-20-06
Program: Bilaterální spolupráce
Institucionální podpora: RVO:61388998
Klíčová slova: expert system * decision making * advanced diagnostic * autonomous navigation * RPA
Obor OECD: Mechanical engineering
https://www.engmech.cz/im/proceedings/show_p/2023/259

Expert systems have gained attention over the last two decades as they bring the possibility of using expert knowledge in various control systems. However, it has lost attraction in favor of artificial neural networks in recent years, which is mostly influenced by the availability of data to train neural network models and the availability of various frameworks to achieve fast time-to-market applications for given solutions.
Trvalý link: https://hdl.handle.net/11104/0351909