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Analiza de Sensibilitate a Scenariilor de Politici×Simulare Monte Carlo×
DomeniuSimulareLuarea deciziilor
FamilieProcess / pipelineMCDM
Anul apariției1990s–2000s1949
Autorul originalSaltelli, A. et al.; Lempert, R. J. et al.Metropolis, N., Ulam, S.
TipAnalytical framework combining scenario planning with sensitivity analysisRobustness wrapper — Monte Carlo uncertainty propagation
Sursa seminalăSaltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., & Tarantola, S. (2008). Global Sensitivity Analysis: The Primer. John Wiley & Sons, Chichester. ISBN: 9780470059975Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
Denumiri alternativePSSA, Policy Sensitivity Analysis, Scenario-Based Sensitivity Analysis, Policy Robustness Analysis
Înrudite50
RezumatPolicy Scenario Sensitivity Analysis (PSSA) combines structured scenario planning with formal sensitivity analysis to determine which model inputs and policy parameters most strongly drive outcomes across a set of distinct policy alternatives or future states. It is widely used in public health, climate, energy, and economic policy modeling to identify robust interventions that perform well even when key assumptions vary.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.
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  1. v1
  2. 1 Surse
  3. PUBLISHED

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ScholarGateCompară metode: Policy Scenario Sensitivity Analysis · MONTE-CARLO-SIMULATION. Preluat la 2026-06-18 de pe https://scholargate.app/ro/compare