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Implementation of supervised principal component analysis for global sensitivity analysis of models with correlated inputs
Global Sensitivity Analysis (GSA) plays a significant role in quantifying the tangible impact of model inputs on the uncertainty of response variable. As GSA results are strongly affected by correlated inputs, several studies have considered this issue, but most of them are computationally expensive...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Berlin Heidelberg
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8787458/ https://www.ncbi.nlm.nih.gov/pubmed/35095342 http://dx.doi.org/10.1007/s00477-021-02158-y |