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| Phân tích độ nhạy mạnh mẽ× | Định lượng Bất định× | |
|---|---|---|
| Lĩnh vực | Mô phỏng | Mô phỏng |
| Họ | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | 1990s–2000s | Seminal modern form: 2002 |
| Người khởi xướng≠ | Saltelli, A. and colleagues | Norbert Wiener (polynomial chaos, 1938); extended to Wiener–Askey scheme by Xiu & Karniadakis (2002) |
| Loại≠ | Simulation-based robustness assessment pipeline | Computational uncertainty analysis framework |
| Công trình gốc≠ | Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., & Tarantola, S. (2008). Global Sensitivity Analysis: The Primer. Wiley. ISBN: 9780470059975 | Xiu, D. & Karniadakis, G.E. (2002). The Wiener-Askey Polynomial Chaos for Stochastic Differential Equations. SIAM Journal on Scientific Computing, 24(2), 619–644. DOI ↗ |
| Tên gọi khác≠ | RSA, Robust SA, Sensitivity Analysis under Uncertainty, Uncertainty-robust sensitivity analysis | UQ, polynomial chaos expansion, PCE, Kriging surrogate |
| Liên quan≠ | 3 | 9 |
| Tóm tắt≠ | Robust Sensitivity Analysis (RSA) systematically evaluates how much variation in model outputs can be attributed to uncertainty or variation in model inputs, with an explicit focus on conclusions that remain valid across a wide range of plausible input conditions. It goes beyond standard sensitivity analysis by asking not only which inputs matter most, but which findings are truly robust — stable regardless of assumptions made under uncertainty. | Uncertainty Quantification (UQ) is a computational framework for systematically measuring how uncertainty in the inputs of a model propagates into uncertainty in its outputs. Building on Wiener's polynomial chaos theory (1938) and formalised for general stochastic problems by Xiu and Karniadakis (2002), UQ uses two primary strategies: Polynomial Chaos Expansion (PCE), which represents the model output as a series of orthogonal polynomials matched to the input distributions, and Kriging (Gaussian process) surrogates, which replace an expensive simulation with a fast statistical approximation fitted to a small set of carefully chosen runs. |
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