提出以加权距离和系统相似度量方法为基础进行聚类分析，提高聚类结果的有效性。
Cluster Analysis is argued to process based on Weighted Distance Coefficient and System Similarity methods to enhance the validity of the clustering result.
该方法对笔迹中局部细微结构的书写变化趋势进行描述，并采用加权距离度量方法进行笔迹相似性度量。
The proposed method depicts the writing trend of local fine structures in handwritings and USES weighted distance metrics to measure the similarity between handwritings.
运用三角模糊数的概念，根据个体加权向量，提出衡量个体间一致性的相似度量函数，由此构造个体、群体的一致性指标。
This function can be used to measure the similarity between individual preference and to construct individual and group consensus index.
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