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| PCA Weighting× | Цялостно базирано на разстояние класиране× | |
|---|---|---|
| Област | Вземане на решения | Вземане на решения |
| Семейство | MCDM | MCDM |
| Година на възникване≠ | 1901 | 2022 |
| Създател≠ | Pearson, K. | Krstić, M., Agnusdei, G. P., Tadić, S., Kovač, M., Miglietta, P. P. |
| Тип≠ | Weight_Objective (PCA variance explained, eigenvector-based) | Distance from PIS/NIS/AS (Euclidean × Taxicab combined) |
| Основополагащ източник≠ | Pearson, K. (1901). On lines and planes of closest fit to systems of points in space. Philosophical Magazine DOI ↗ | Krstić, M., Agnusdei, G. P., Tadić, S., Kovač, M., Miglietta, P. P. (2022). A Novel Axiomatic DEA-COBRA Framework for Evaluating the Sustainable Performance of Agri-Food Systems. Sustainability link ↗ |
| Други названия | — | — |
| Свързани | 8 | 8 |
| Резюме≠ | PCA-WEIGHT (PCA Weighting — Principal Component Analysis based objective weighting) is a weight objective multi-criteria decision-making (MCDM) method introduced by Pearson, K. in 1901. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. | COBRA (COmprehensive distance Based RAnking) is a ranking multi-criteria decision-making (MCDM) method introduced by Krstić, M., Agnusdei, G. P., Tadić, S., Kovač, M., Miglietta, P. P. in 2022. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
| ScholarGateНабор от данни ↗ |
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