Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Uz datiem balstīta daudzkritēriju lēmumu analīze× | PROMETHEE II× | |
|---|---|---|
| Nozare | Lēmumu pieņemšana | Lēmumu pieņemšana |
| Saime | MCDM | MCDM |
| Izcelsmes gads≠ | 2015 | 1986 |
| Autors≠ | Multiple authors | Brans, J. P., Vincke, Ph., Mareschal, B. |
| Tips≠ | Learning-based criteria weighting and aggregation | Preference function (net flow) |
| Pirmavots≠ | Греченко, Д. В. (2019). Data-driven decision making: Integrating machine learning with multi-criteria approaches. Computational Statistics & Data Analysis, 132, 127-143. link ↗ | Brans, J. P., Vincke, Ph., Mareschal, B. (1986). How to select and how to rank projects: The PROMETHEE method. European Journal of Operational Research DOI ↗ |
| Citi nosaukumi≠ | Data-Driven MCDA | — |
| Saistītās≠ | 5 | 8 |
| Kopsavilkums≠ | Data-Driven MCDA is a hybrid framework that integrates machine learning and statistical learning into traditional multi-criteria decision analysis. Instead of eliciting weights from expert judgment, it learns criteria importance from historical decision data, enabling more scalable and empirically grounded decision support. | PROMETHEE (PROMETHEE II — Preference Ranking Organisation METHod for Enrichment of Evaluations) is a outranking multi-criteria decision-making (MCDM) method introduced by Brans, J. P., Vincke, Ph., Mareschal, B. in 1986. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
| ScholarGateDatu kopa ↗ |
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