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Pembobotan PCA×Penarafan Berdasarkan Jarak Komprehensif×
BidangPembuatan KeputusanPembuatan Keputusan
KeluargaMCDMMCDM
Tahun asal19012022
PengasasPearson, K.Krstić, M., Agnusdei, G. P., Tadić, S., Kovač, M., Miglietta, P. P.
JenisWeight_Objective (PCA variance explained, eigenvector-based)Distance from PIS/NIS/AS (Euclidean × Taxicab combined)
Sumber perintisPearson, K. (1901). On lines and planes of closest fit to systems of points in space. Philosophical Magazine DOI ↗Krstić, M., Agnusdei, G. P., Tadić, S., Kovač, M., Miglietta, P. P. (2022). A Novel Axiomatic DEA-COBRA Framework for Evaluating the Sustainable Performance of Agri-Food Systems. Sustainability 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.COBRA (COmprehensive distance Based RAnking) is a ranking multi-criteria decision-making (MCDM) method introduced by Krstić, M., Agnusdei, G. P., Tadić, S., Kovač, M., Miglietta, P. P. in 2022. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateBandingkan kaedah: PCA-WEIGHT · COBRA. Dicapai 2026-06-17 daripada https://scholargate.app/ms/compare