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PCA权重×自动成对线性排序组合×
领域决策决策
方法族MCDMMCDM
起源年份19012020
提出者Pearson, K.Konstantinos, N., Xenakis, A., Kehagias, A.
类型Weight_Objective (PCA variance explained, eigenvector-based)Pairwise dominance aggregation (automatic combination)
开创性文献Pearson, K. (1901). On lines and planes of closest fit to systems of points in space. Philosophical Magazine DOI ↗Konstantinos, N., Xenakis, A., Kehagias, A. (2020). APLOCO: A linear programming-based multicriteria ranking method that handles dependent criteria and criteria groups. Operational Research link ↗
别名
相关88
摘要PCA-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.APLOCO (Automatic Pairwise Linear Order Combination) is a ranking multi-criteria decision-making (MCDM) method introduced by Konstantinos, N., Xenakis, A., Kehagias, A. in 2020. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
ScholarGate数据集
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ScholarGate方法对比: PCA-WEIGHT · APLOCO. 于 2026-06-17 检索自 https://scholargate.app/zh/compare