MCDMNormalizationcrisp
向量归一化 — 欧几里得列范数缩放 (L2 归一化)
NORM-VECTOR (向量归一化 — 欧几里得列范数缩放 (L2 归一化)) 是一种多准则决策 (MCDM) 方法，由 Hwang, C. L. 和 Yoon, K. 于 1981 年提出。它将一个由备选方案在多个准则上评分组成的决策矩阵转化为结构化、可复现的结果。
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来源
- Hwang, C. L., Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. Lecture Notes in Economics and Mathematical Systems, Vol. 186, Springer-Verlag DOI: 10.1007/978-3-642-48318-9 ↗
如何引用本页
ScholarGate. (2026, June 2). Vector Normalization — Euclidean column-norm scaling (L2 normalisation). ScholarGate. https://scholargate.app/zh/decision-making/norm-vector
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