Salīdzināt metodes
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| L2T-COPRAS lingvistiskais paplašinājums× | Kritēriju korelācijas un standartnovirzes objektīvā svēršana× | |
|---|---|---|
| Nozare | Lēmumu pieņemšana | Lēmumu pieņemšana |
| Saime | MCDM | MCDM |
| Izcelsmes gads≠ | 2021 | 2010 |
| Autors≠ | Gai, T., Cao, M., Cao, Q., Wu, J., Yu, G., Zhou, M. | Wang, Y. M., Luo, Y. |
| Tips≠ | Linguistic outranking/ranking — 2-Tuple Linguistic Variable (2TL: (s_i, α)) | Correlation-penalised standard-deviation weighting |
| Pirmavots≠ | Gai, T., Cao, M., Cao, Q., Wu, J., Yu, G., Zhou, M. (2021). An integrated method for hybrid distribution with estimation of demand matching degree (interval 2-tuple linguistic COPRAS). link ↗ | Wang, Y. M., Luo, Y. (2010). Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making. Mathematical and Computer Modelling DOI ↗ |
| Citi nosaukumi | — | — |
| Saistītās | 8 | 8 |
| Kopsavilkums≠ | L2T-COPRAS (Linguistic extension of L2T-COPRAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Gai, T., Cao, M., Cao, Q., Wu, J., Yu, G., Zhou, M. in 2021. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. | CCSD (Criteria Correlation and Standard Deviation objective weighting) is a weight objective multi-criteria decision-making (MCDM) method introduced by Wang, Y. M., Luo, Y. in 2010. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
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