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Deterministyczna analiza wrażliwości×Symulacja Monte Carlo×
DziedzinaSymulacjaPodejmowanie decyzji
RodzinaProcess / pipelineMCDM
Rok powstania1950s–1970s (formalized)1949
TwórcaSaltelli, A. et al.; widely formalized across operations research and health economicsMetropolis, N., Ulam, S.
TypParameter variation / robustness testingRobustness wrapper — Monte Carlo uncertainty propagation
Źródło pierwotneSaltelli, A., Tarantola, S., Campolongo, F., & Ratto, M. (2004). Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models. John Wiley & Sons, Chichester. ISBN: 9780470870938Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
Inne nazwyDSA, One-Way Sensitivity Analysis, Tornado Diagram Analysis, Parametric Sensitivity Analysis
Pokrewne20
PodsumowanieDeterministic Sensitivity Analysis (DSA) tests how model outputs change when individual or combined input parameters are varied across plausible ranges, one at a time or in structured combinations, without invoking probabilistic sampling. It is the standard approach in economic modeling, decision trees, and mathematical programming to identify which parameters drive conclusions and to demonstrate model robustness to regulators, reviewers, and stakeholders.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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ScholarGatePorównaj metody: Deterministic Sensitivity Analysis · MONTE-CARLO-SIMULATION. Pobrano 2026-06-15 z https://scholargate.app/pl/compare