ScholarGate
Avustaja

Vertaile menetelmiä

Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.

Dual Hesitant Fuzzy -TOPSIS-menetelmä×Kriteerien korrelaatio ja keskihajonta objektiivinen painotus×
TieteenalaPäätöksentekoPäätöksenteko
MenetelmäperheMCDMMCDM
Syntyvuosi20202010
KehittäjäWang, R., Li, W., Zhang, T., Han, Q.Wang, Y. M., Luo, Y.
TyyppiDual Hesitant outranking/ranking — Dual Hesitant Fuzzy Element (DHFE: h(x) membership set, g(x) non-membership set)Correlation-penalised standard-deviation weighting
AlkuperäislähdeWang, R., Li, W., Zhang, T., Han, Q. (2020). New Distance Measures for Dual Hesitant Fuzzy Sets and Their Application to Multiple Attribute Decision Making. Symmetry 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 ↗
Rinnakkaisnimet
Liittyvät88
TiivistelmäDHF-TOPSIS (Dual Hesitant Fuzzy extension of TOPSIS) is a ranking multi-criteria decision-making (MCDM) method introduced by Wang, R., Li, W., Zhang, T., Han, Q. in 2020. 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.
ScholarGateAineisto
  1. v1
  2. 1 Lähteet
  3. PUBLISHED
  1. v1
  2. 1 Lähteet
  3. PUBLISHED

Siirry hakuun Lataa diat

ScholarGateVertaile menetelmiä: DHF-TOPSIS · CCSD. Haettu 2026-06-18 osoitteesta https://scholargate.app/fi/compare