方法对比
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| Stochastic Sensitivity Analysis× | 敏感性分析× | |
|---|---|---|
| 领域≠ | 仿真 | 决策 |
| 方法族≠ | Process / pipeline | MCDM |
| 起源年份≠ | 1990s–2000s | 2004 |
| 提出者≠ | Saltelli, A. et al.; Claxton, K. et al. (health economics stream) | Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M. |
| 类型≠ | Probabilistic uncertainty quantification technique | Robustness wrapper — parameter / weight perturbation sensitivity indices |
| 开创性文献≠ | 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 | Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M. (2004). Sensitivity Analysis in Practice. Wiley, Chichester DOI ↗ |
| 别名≠ | PSA, Probabilistic Sensitivity Analysis, Stochastic SA, Monte Carlo Sensitivity Analysis | — |
| 相关≠ | 5 | 0 |
| 摘要≠ | Stochastic Sensitivity Analysis (PSA) extends classical one-at-a-time sensitivity testing by representing uncertain model inputs as probability distributions and propagating them through the model via Monte Carlo sampling. The result is a full distribution of possible outputs, together with rankings of which inputs drive output variance the most — enabling robust, evidence-grounded conclusions under uncertainty. | SENSITIVITY-ANALYSIS (Sensitivity Analysis — Systematic assessment of output variation w.r.t. input perturbations) is a ranking multi-criteria decision-making (MCDM) method introduced by Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M. in 2004. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
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