方法对比
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| 模拟辅助趋势研究× | 蒙特卡洛模拟× | |
|---|---|---|
| 领域≠ | 研究设计 | 决策 |
| 方法族≠ | Process / pipeline | MCDM |
| 起源年份≠ | 1990s–2000s (convergence of computational simulation with survey-based trend designs) | 1949 |
| 提出者≠ | Synthesized from trend research (Creswell) and Monte Carlo / agent-based simulation traditions (Mooney, 1997) | Metropolis, N., Ulam, S. |
| 类型≠ | Quantitative research design with computational augmentation | Robustness wrapper — Monte Carlo uncertainty propagation |
| 开创性文献≠ | Creswell, J. W., & Creswell, J. D. (2023). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (6th ed.). SAGE Publications. ISBN: 978-1071817971 | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| 别名≠ | simulation-augmented trend study, Monte Carlo trend research, computational trend analysis, simulation-based longitudinal trend design | — |
| 相关≠ | 4 | 0 |
| 摘要≠ | Simulation-assisted trend research combines repeated cross-sectional survey data collected at multiple time points with computational simulation techniques — such as Monte Carlo methods or agent-based modeling — to project, validate, and stress-test observed trends. It extends classic trend research by replacing or supplementing extrapolation with probabilistic scenario modeling, allowing researchers to quantify uncertainty around trend trajectories and explore counterfactual futures under varying assumptions. | 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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