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확률적 미시모의시뮬레이션×확률론적 시스템 동학×
분야시뮬레이션시뮬레이션
계열Process / pipelineProcess / pipeline
기원 연도19571980s–2000s
창시자Guy H. OrcuttJay W. Forrester (base SD); stochastic extensions developed through 1980s–2000s by multiple researchers
유형Stochastic individual-level simulationContinuous stochastic simulation
원전Orcutt, G. H. (1957). A new type of socio-economic system. The Review of Economics and Statistics, 39(2), 116–123. DOI ↗Sterman, J.D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin McGraw-Hill. ISBN: 978-0072389159
별칭Probabilistic Microsimulation, Monte Carlo Microsimulation, Stochastic Micro-simulation, SMSMSSD, stochastic stock-flow modelling, probabilistic system dynamics, random system dynamics
관련65
요약Stochastic Microsimulation tracks a large population of individual units — people, households, or firms — through time by applying random draws from empirically estimated probability distributions at each transition event. Unlike deterministic counterparts, every state change is decided by chance, preserving realistic heterogeneity and allowing rigorous uncertainty quantification across multiple simulation runs.Stochastic System Dynamics (SSD) extends conventional system dynamics by replacing fixed parameter values and deterministic flow equations with probability distributions and random draws. Running many replications of the stock-flow model yields probabilistic trajectories — confidence bands rather than single lines — enabling rigorous uncertainty quantification and risk analysis in complex feedback systems such as epidemic models, supply chains, and energy policy scenarios.
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ScholarGate방법 비교: Stochastic Microsimulation · Stochastic System Dynamics. 2026-06-15에 다음에서 검색함: https://scholargate.app/ko/compare