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Pembobotan PCA×Penilaian Berasaskan Jarak Gabungan×
BidangPembuatan KeputusanPembuatan Keputusan
KeluargaMCDMMCDM
Tahun asal19012016
PengasasPearson, K.Keshavarz Ghorabaee, M., Zavadskas, E. K., Turskis, Z., Antucheviciene, J.
JenisWeight_Objective (PCA variance explained, eigenvector-based)Distance from anti-ideal (Euclidean + Taxicab)
Sumber perintisPearson, K. (1901). On lines and planes of closest fit to systems of points in space. Philosophical Magazine DOI ↗Keshavarz Ghorabaee, M., Zavadskas, E. K., Turskis, Z., Antucheviciene, J. (2016). A new combinative distance-based assessment (CODAS) method for multi-criteria decision-making. Economic Computation and Economic Cybernetics Studies and Research link ↗
Alias
Berkaitan88
RingkasanPCA-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.CODAS (Combinative Distance-Based Assessment) is a ranking multi-criteria decision-making (MCDM) method introduced by Keshavarz Ghorabaee, M., Zavadskas, E. K., Turskis, Z., Antucheviciene, J. in 2016. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateBandingkan kaedah: PCA-WEIGHT · CODAS. Dicapai 2026-06-15 daripada https://scholargate.app/ms/compare