পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| বৈশ্বিক সংবেদনশীলতা বিশ্লেষণ× | মন্টে কার্লো সিমুলেশন× | |
|---|---|---|
| ক্ষেত্র≠ | অনুকরণ | সিদ্ধান্ত গ্রহণ |
| পরিবার≠ | Process / pipeline | MCDM |
| উদ্ভবের বছর≠ | 1973–2001 | 1949 |
| প্রবর্তক≠ | I.M. Sobol (indices, 2001); Morris (screening, 1991); Cukier et al. (FAST, 1973) | Metropolis, N., Ulam, S. |
| ধরন≠ | Variance-based sensitivity decomposition | Robustness wrapper — Monte Carlo uncertainty propagation |
| মৌলিক উৎস≠ | Sobol, I.M. (2001). Global Sensitivity Indices for Nonlinear Mathematical Models and Their Monte Carlo Estimates. Mathematics and Computers in Simulation, 55(1–3), 271–280. DOI ↗ | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| অপর নাম≠ | variance decomposition, Sobol indices, Morris screening, FAST method | — |
| সম্পর্কিত≠ | 4 | 0 |
| সারসংক্ষেপ≠ | Global sensitivity analysis (GSA) is a family of techniques that decompose the variance of a model's output across its input parameters, quantifying how much each input — and each combination of inputs — contributes to the total uncertainty in the result. Sobol's variance-based indices (2001), Morris's one-at-a-time (OAT) screening (1991), and the Fourier Amplitude Sensitivity Test (FAST, first proposed by Cukier et al. in 1973) are the three most widely used approaches. Together they serve as the standard toolkit for identifying which parameters drive model behaviour and which can be safely fixed. | 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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