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。
| 离散事件系统仿真× | 自助法模拟× | |
|---|---|---|
| 领域 | 仿真 | 仿真 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1960s (formalised in literature through the 1980s–2000s) | 1979 |
| 提出者≠ | Kelton, Law & Sadowski (formalised methodology); SIMSCRIPT (Markowitz et al., 1963) and GPSS (Gordon, 1961) were pioneering tools | Bradley Efron |
| 类型≠ | Stochastic process simulation | Simulation-based nonparametric inference |
| 开创性文献≠ | Kelton, W.D., Sadowski, R.P. & Zupick, N.B. (2014). Simulation with Arena (6th ed.). McGraw-Hill. ISBN: 978-0073401317 | Efron, B. & Tibshirani, R.J. (1993). An Introduction to the Bootstrap. Chapman & Hall/CRC. DOI ↗ |
| 别名≠ | DES, discrete event simulation, Kesikli Sistem Simülasyonu (Arena / AnyLogic tarzı) | bootstrap resampling, empirical resampling, nonparametric bootstrap, Önyükleme Simülasyonu (Bootstrap Resampling) |
| 相关≠ | 4 | 5 |
| 摘要≠ | Discrete-event system simulation (DES) is a computational modelling technique in which the state of a system changes only at discrete points in time — called events — such as a customer arriving, a machine starting, or a job completing. Formalised through foundational texts by Kelton, Sadowski, and Zupick (2014) and Law (2015), DES represents processes as networks of resources, queues, and activities, allowing analysts to test capacity and policy changes on a virtual model before touching the real system. | Bootstrap simulation, introduced by Bradley Efron in 1979, is a simulation-based inference method that derives the sampling distribution of virtually any statistic by repeatedly resampling with replacement from the observed data. Because it requires no parametric distributional assumptions, it provides a robust, general-purpose alternative to analytical confidence intervals and parametric hypothesis tests across continuous, ordinal, binary, and count data. |
| ScholarGate数据集 ↗ |
|
|