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Cubic-EDAS – Kubisches pythagoreisches Fuzzy-EDAS (CuP-EDAS)×Kriteriengewichtung mittels Korrelation und Standardabweichung×
FachgebietEntscheidungsfindungEntscheidungsfindung
FamilieMCDMMCDM
Entstehungsjahr20232010
UrheberPaul, T.K., Jana, C., Pal, M.Wang, Y. M., Luo, Y.
TypCubic Pythagorean Fuzzy ranking — CuPyFN = ⟨IvPyFN, PyFN⟩ = (⟨[Y⁻,Y⁺],[F⁻,F⁺]⟩,⟨Y,F⟩); Pythagorean constraint (Y⁺)²+(F⁺)² ≤ 1; average-solution EDAS with score-function PDA/NDACorrelation-penalised standard-deviation weighting
Wegweisende QuellePaul, T.K., Jana, C., Pal, M. (2023). Multi-criteria group decision-making method in disposal of municipal solid waste based on cubic Pythagorean fuzzy EDAS approach with incomplete weight information. Applied Soft Computing DOI ↗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 ↗
Aliasnamen
Verwandt88
ZusammenfassungCUBIC-EDAS (Cubic-EDAS — Cubic Pythagorean Fuzzy EDAS (CuP-EDAS)) is a ranking multi-criteria decision-making (MCDM) method introduced by Paul, T.K., Jana, C., Pal, M. in 2023. 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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ScholarGateMethoden vergleichen: CUBIC-EDAS · CCSD. Abgerufen am 2026-06-17 von https://scholargate.app/de/compare