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क्षेत्रअनुकरणनिर्णयन
परिवारProcess / pipelineMCDM
उद्भव वर्ष1990s–2000s1949
प्रवर्तकSaltelli, A. et al.; Lempert, R. J. et al.Metropolis, N., Ulam, S.
प्रकारAnalytical framework combining scenario planning with sensitivity analysisRobustness wrapper — Monte Carlo uncertainty propagation
मौलिक स्रोतSaltelli, 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 ↗
उपनामPSSA, Policy Sensitivity Analysis, Scenario-Based Sensitivity Analysis, Policy Robustness Analysis
संबंधित50
सारांशPolicy 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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ScholarGateविधियों की तुलना करें: Policy Scenario Sensitivity Analysis · MONTE-CARLO-SIMULATION. 2026-06-18 को यहाँ से प्राप्त https://scholargate.app/hi/compare