ScholarGate
助手

方法对比

并排查看您选择的方法;存在差异的行会高亮显示。

PCA权重×基于自适应标准化区间的替代方案排序技术×
领域决策决策
方法族MCDMMCDM
起源年份19012024
提出者Pearson, K.Kara, K., Yalçın, G. C., Kaygısız, E. G., Simic, V., Örnek, A. Ş., Pamucar, D.
类型Weight_Objective (PCA variance explained, eigenvector-based)Two-level standardization + ideal/anti-ideal utility (β-anchored)
开创性文献Pearson, K. (1901). On lines and planes of closest fit to systems of points in space. Philosophical Magazine DOI ↗Kara, K., Yalçın, G. C., Kaygısız, E. G., Simic, V., Örnek, A. Ş., Pamucar, D. (2024). A picture fuzzy CIMAS-ARTASI model for website performance analysis in human resource management. Applied Soft Computing DOI ↗
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.ARTASI (Alternative Ranking Technique based on Adaptive Standardized Intervals) is a ranking multi-criteria decision-making (MCDM) method introduced by Kara, K., Yalçın, G. C., Kaygısız, E. G., Simic, V., Örnek, A. Ş., Pamucar, D. in 2024. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
ScholarGate数据集
  1. v1
  2. 1 来源
  3. PUBLISHED
  1. v1
  2. 1 来源
  3. PUBLISHED

前往搜索 下载幻灯片

ScholarGate方法对比: PCA-WEIGHT · ARTASI. 于 2026-06-18 检索自 https://scholargate.app/zh/compare