A Bayesian inference-based approach for performance prognostics towards uncertainty quantification and its applications on the marine diesel engine.

Wang, Ruihan; Chen, Hui; Guan, Cong

Wang, Ruihan; Chen, Hui; Guan, Cong.

Afiliación

Wang R; School of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, PR China; Key Laboratory of High Performance Ship Technology of Ministry of Education, Wuhan University of Technology, Wuhan 430063, PR China.
Chen H; School of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, PR China; Key Laboratory of High Performance Ship Technology of Ministry of Education, Wuhan University of Technology, Wuhan 430063, PR China.
Guan C; School of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, PR China; Key Laboratory of High Performance Ship Technology of Ministry of Education, Wuhan University of Technology, Wuhan 430063, PR China. Electronic address: guancong2008@126.com.

ISA Trans ; 118: 159-173, 2021 Dec.

Article en En | MEDLINE | ID: mdl-33642029

Palabras clave

Bayesian inference; Logistic regression function; Neural networks; Performance prognostics; Uncertainty quantification

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: ISA Trans Año: 2021 Tipo del documento: Article Pais de publicación: Estados Unidos

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