Võrdle meetodeid
Vaata valitud meetodeid kõrvuti; erinevad read on esile tõstetud.
| PCA kaalumine – peapõhikomponentide analüüsil põhinev objektiivne kaalumine× | Kombinatiivne kauguspõhine hindamine× | |
|---|---|---|
| Valdkond | Otsustamine | Otsustamine |
| Perekond | MCDM | MCDM |
| Tekkeaasta≠ | 1901 | 2016 |
| Looja≠ | Pearson, K. | Keshavarz Ghorabaee, M., Zavadskas, E. K., Turskis, Z., Antucheviciene, J. |
| Tüüp≠ | Weight_Objective (PCA variance explained, eigenvector-based) | Distance from anti-ideal (Euclidean + Taxicab) |
| Algallikas≠ | Pearson, K. (1901). On lines and planes of closest fit to systems of points in space. Philosophical Magazine DOI ↗ | Keshavarz Ghorabaee, M., Zavadskas, E. K., Turskis, Z., Antucheviciene, J. (2016). A new combinative distance-based assessment (CODAS) method for multi-criteria decision-making. Economic Computation and Economic Cybernetics Studies and Research link ↗ |
| Rööpnimetused | — | — |
| Seotud | 8 | 8 |
| Kokkuvõte≠ | 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. | CODAS (Combinative Distance-Based Assessment) is a ranking multi-criteria decision-making (MCDM) method introduced by Keshavarz Ghorabaee, M., Zavadskas, E. K., Turskis, Z., Antucheviciene, J. in 2016. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
| ScholarGateAndmestik ↗ |
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