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Probabilistiline kõhklev COPRAS-i laiendus×Kriteeriumide eemaldamise mõjudel põhinev meetod×
ValdkondOtsustamineOtsustamine
PerekondMCDMMCDM
Tekkeaasta20212021
LoojaSong, H. F. Chen, Z. C.Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z.
TüüpProbabilistic Hesitant ranking — Probabilistic Hesitant Fuzzy Element (PHFE: {γ|p} pairs)Removal-effect objective weighting (logarithmic utility)
AlgallikasSong, H. F., Chen, Z. C. (2021). Multi-attribute decision-making method based distance and COPRAS method with probabilistic hesitant fuzzy environment. International Journal of Computational Intelligence Systems DOI ↗Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z. (2021). Determination of objective weights using a new method based on the removal effects of criteria (MEREC). Informatica DOI ↗
Rööpnimetused
Seotud88
KokkuvõtePHF-COPRAS (Probabilistic Hesitant extension of COPRAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Song, H. F. Chen, Z. C. in 2021. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.MEREC (MEthod based on the Removal Effects of Criteria) is a weight objective multi-criteria decision-making (MCDM) method introduced by Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z. in 2021. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateVõrdle meetodeid: PHF-COPRAS · MEREC. Loetud 2026-06-15 aadressilt https://scholargate.app/et/compare