Data-driven sparse polynomial chaos expansion for models with dependent inputs
Polynomial chaos expansions (PCEs) have been used in many real-world engineering applications to quantify how the uncertainty of an output is propagated from inputs by decomposing the output in terms of polynomials of the inputs. PCEs for models with independent inputs have been extensively explored...
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| Главные авторы: | , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
KeAi Communications Co., Ltd.
2023-12-01
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| Серии: | Journal of Safety Science and Resilience |
| Предметы: | |
| Online-ссылка: | http://www.sciencedirect.com/science/article/pii/S2666449623000415 |
| Метки: |
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