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PCA kaalumine – peapõhikomponentide analüüsil põhinev objektiivne kaalumine×Alternatiivse järjestusmeetodi kaheetapilise normaliseerimise arvestus×
ValdkondOtsustamineOtsustamine
PerekondMCDMMCDM
Tekkeaasta19012022
LoojaPearson, K.Zdravković, M., Hamid, M., Radovanović, M.
TüüpWeight_Objective (PCA variance explained, eigenvector-based)Two-step normalisation (linear + vector) with weighted power aggregation
AlgallikasPearson, K. (1901). On lines and planes of closest fit to systems of points in space. Philosophical Magazine DOI ↗Zdravković, M., Hamid, M., Radovanović, M. (2022). AROMAN — Alternative Ranking Order Method Accounting for Two-Step Normalisation. Journal of Computational Design and Engineering link ↗
Rööpnimetused
Seotud88
KokkuvõtePCA-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.AROMAN (Alternative Ranking Order Method Accounting for Two-Step Normalisation) is a ranking multi-criteria decision-making (MCDM) method introduced by Zdravković, M., Hamid, M., Radovanović, M. in 2022. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateVõrdle meetodeid: PCA-WEIGHT · AROMAN. Loetud 2026-06-18 aadressilt https://scholargate.app/et/compare