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تحليل الحساسية العشوائية×محاكاة الأحداث المنفصلة العشوائية×
المجالالمحاكاةالمحاكاة
العائلةProcess / pipelineProcess / pipeline
سنة النشأة1990s–2000s1960s–1970s
صاحب الطريقةSaltelli, A. et al.; Claxton, K. et al. (health economics stream)Banks, Carson, Nelson, Nicol; Law, A. M.
النوعProbabilistic uncertainty quantification techniqueStochastic simulation model
المصدر التأسيسيSaltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., Tarantola, S. (2008). Global Sensitivity Analysis: The Primer. Wiley. ISBN: 9780470059975Banks, J., Carson, J. S., Nelson, B. L., & Nicol, D. M. (2010). Discrete-Event System Simulation (5th ed.). Prentice Hall. ISBN: 9780136062127
الأسماء البديلةPSA, Probabilistic Sensitivity Analysis, Stochastic SA, Monte Carlo Sensitivity AnalysisStochastic DES, SDES, Probabilistic DES, Monte Carlo DES
ذات صلة56
الملخصStochastic Sensitivity Analysis (PSA) extends classical one-at-a-time sensitivity testing by representing uncertain model inputs as probability distributions and propagating them through the model via Monte Carlo sampling. The result is a full distribution of possible outputs, together with rankings of which inputs drive output variance the most — enabling robust, evidence-grounded conclusions under uncertainty.Stochastic Discrete-Event Simulation (Stochastic DES) models complex systems by advancing simulated time from one discrete event to the next, drawing event durations and inter-arrival times from fitted probability distributions. It is the standard technique for analyzing queues, manufacturing lines, healthcare pathways, and logistics networks under uncertainty, producing output statistics with confidence intervals.
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ScholarGateقارن الطرق: Stochastic Sensitivity Analysis · Stochastic Discrete-Event Simulation. استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare