مقایسهٔ روشها
روشهای انتخابی خود را کنار هم مرور کنید؛ ردیفهای متفاوت برجسته شدهاند.
| تحلیل سناریوی بیزی× | شبیهسازی مونت کارلو× | |
|---|---|---|
| حوزه≠ | شبیهسازی | تصمیمگیری |
| خانواده≠ | Process / pipeline | MCDM |
| سال پیدایش≠ | 2000s | 1949 |
| پدیدآور≠ | Developed iteratively across Bayesian statistics and scenario planning communities; formalized in risk and decision analysis (Aven, Lempert et al., 2000s) | Metropolis, N., Ulam, S. |
| نوع≠ | Probabilistic hybrid — Bayesian inference integrated with structured scenario analysis | Robustness wrapper — Monte Carlo uncertainty propagation |
| 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 ↗ | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| نامهای دیگر≠ | BSA, Bayesian scenario planning, probabilistic scenario analysis, Bayesian-weighted scenario analysis | — |
| مرتبط≠ | 5 | 0 |
| 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. | MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
| ScholarGateمجموعهداده ↗ |
|
|