Learning methods for remaining useful life prediction in a turbofan engine (2022)
- Authors:
- Autor USP: SANTOS, LUIS CARLOS DE CASTRO - IME
- Unidade: IME
- DOI: 10.5753/eniac.2022.227615
- Subjects: INDÚSTRIA 4.0; APRENDIZADO COMPUTACIONAL; REDES NEURAIS; AERONÁUTICA
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: SBC
- Publisher place: Porto Alegre
- Date published: 2022
- Source:
- Título do periódico: Anais
- Conference titles: Encontro Nacional de Inteligência Artificial e Computacional - ENIAC
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: bronze
-
ABNT
LEAL, Andréia Seixas e BERTON, Lilian e SANTOS, Luis Carlos de Castro. Learning methods for remaining useful life prediction in a turbofan engine. 2022, Anais.. Porto Alegre: SBC, 2022. Disponível em: https://doi.org/10.5753/eniac.2022.227615. Acesso em: 27 abr. 2024. -
APA
Leal, A. S., Berton, L., & Santos, L. C. de C. (2022). Learning methods for remaining useful life prediction in a turbofan engine. In Anais. Porto Alegre: SBC. doi:10.5753/eniac.2022.227615 -
NLM
Leal AS, Berton L, Santos LC de C. Learning methods for remaining useful life prediction in a turbofan engine [Internet]. Anais. 2022 ;[citado 2024 abr. 27 ] Available from: https://doi.org/10.5753/eniac.2022.227615 -
Vancouver
Leal AS, Berton L, Santos LC de C. Learning methods for remaining useful life prediction in a turbofan engine [Internet]. Anais. 2022 ;[citado 2024 abr. 27 ] Available from: https://doi.org/10.5753/eniac.2022.227615 - Accurate CFD measurements of vortex generators effects on a wing subject to shock-induced separation
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Informações sobre o DOI: 10.5753/eniac.2022.227615 (Fonte: oaDOI API)
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