方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 政策情景系统动力学× | 随机系统动力学× | |
|---|---|---|
| 领域 | 仿真 | 仿真 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1960s–1990s | 1980s–2000s |
| 提出者≠ | Forrester, J. W. (system dynamics); scenario integration formalized by Sterman and others | Jay W. Forrester (base SD); stochastic extensions developed through 1980s–2000s by multiple researchers |
| 类型≠ | Simulation-based policy analysis | Continuous stochastic simulation |
| 开创性文献≠ | Sterman, J. D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. McGraw-Hill. ISBN: 9780072389159 | Sterman, J.D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin McGraw-Hill. ISBN: 978-0072389159 |
| 别名 | PSSD, Policy SD Simulation, Scenario-Based System Dynamics, Policy Systems Modeling | SSD, stochastic stock-flow modelling, probabilistic system dynamics, random system dynamics |
| 相关 | 5 | 5 |
| 摘要≠ | Policy Scenario System Dynamics combines system dynamics modeling with structured scenario analysis to evaluate how different policy interventions affect complex, feedback-driven systems over time. By running multiple policy scenarios through a calibrated stock-and-flow model, analysts can compare long-run outcomes, identify leverage points, and anticipate unintended consequences before real-world implementation. | 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. |
| ScholarGate数据集 ↗ |
|
|