مقایسهٔ روشها
روشهای انتخابی خود را کنار هم مرور کنید؛ ردیفهای متفاوت برجسته شدهاند.
| تحلیل سناریوی بیزی× | تحلیل حساسیت بیزی× | |
|---|---|---|
| حوزه | شبیهسازی | شبیهسازی |
| خانواده | Process / pipeline | Process / pipeline |
| سال پیدایش≠ | 2000s | 1984–1994 |
| پدیدآور≠ | Developed iteratively across Bayesian statistics and scenario planning communities; formalized in risk and decision analysis (Aven, Lempert et al., 2000s) | Berger, J. O. (Bayesian robustness); Saltelli et al. (global SA integration) |
| نوع≠ | Probabilistic hybrid — Bayesian inference integrated with structured scenario analysis | Uncertainty propagation and sensitivity quantification |
| منبع بنیادین≠ | Aven, T., & Reniers, G. (2013). How to define and interpret a probability in a risk and safety setting. Safety Science, 51(1), 223–231. DOI ↗ | Berger, J. O. (1994). An overview of robust Bayesian analysis. Test, 3(1), 5–124. DOI ↗ |
| نامهای دیگر | BSA, Bayesian scenario planning, probabilistic scenario analysis, Bayesian-weighted scenario analysis | BSA, Bayesian SA, Bayesian robustness analysis, prior sensitivity analysis |
| مرتبط | 5 | 5 |
| خلاصه≠ | Bayesian Scenario Analysis (BSA) combines structured scenario planning with Bayesian probability theory, assigning explicit prior probabilities to alternative futures and updating them as new evidence or expert judgments become available. The result is a probability-weighted distribution of outcomes across scenarios rather than a set of equally-weighted or arbitrarily-weighted futures. | Bayesian Sensitivity Analysis (BSA) combines Bayesian inference with sensitivity analysis to systematically quantify how uncertain model inputs — expressed as prior probability distributions — propagate through a model and influence outputs. It identifies which parameters most drive output variability, supporting robust conclusions under genuine uncertainty. |
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