A two-level kriging-based approach with active learning for solving time-variant risk optimization problems (2020)
- Authors:
- Autor USP: BECK, ANDRÉ TEÓFILO - EESC
- Unidade: EESC
- DOI: 10.1016/j.ress.2020.107033
- Subjects: ESTRUTURAS; RISCO
- Language: Inglês
- Imprenta:
- Publisher place: London, United Kingdom
- Date published: 2020
- Source:
- Título: Reliability Engineering and System Safety
- ISSN: 0951-8320
- Volume/Número/Paginação/Ano: v. 118, p. 18-27, October 2013
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
KROETZ, H. M. et al. A two-level kriging-based approach with active learning for solving time-variant risk optimization problems. Reliability Engineering and System Safety, v. 118, p. 18-27, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.ress.2020.107033. Acesso em: 21 jan. 2026. -
APA
Kroetz, H. M., Moustapha, M., Beck, A. T., & Sudret, B. (2020). A two-level kriging-based approach with active learning for solving time-variant risk optimization problems. Reliability Engineering and System Safety, 118, 18-27. doi:10.1016/j.ress.2020.107033 -
NLM
Kroetz HM, Moustapha M, Beck AT, Sudret B. A two-level kriging-based approach with active learning for solving time-variant risk optimization problems [Internet]. Reliability Engineering and System Safety. 2020 ; 118 18-27.[citado 2026 jan. 21 ] Available from: https://doi.org/10.1016/j.ress.2020.107033 -
Vancouver
Kroetz HM, Moustapha M, Beck AT, Sudret B. A two-level kriging-based approach with active learning for solving time-variant risk optimization problems [Internet]. Reliability Engineering and System Safety. 2020 ; 118 18-27.[citado 2026 jan. 21 ] Available from: https://doi.org/10.1016/j.ress.2020.107033 - Challenges in finding the design point with highly non-Gaussian bounded random variables
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Informações sobre o DOI: 10.1016/j.ress.2020.107033 (Fonte: oaDOI API)
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