Vague集之间的相似度量新方法*

为了构建一个新的Vague集之间相似度量方法，运用比较法和Vague理论，分析现有的相似度量方法的缺陷所在，给出了一种新的相似度量公式, 该公式不但包括了衡量Vague值（集）的相似的必要参数，且考虑到无论是Vague值区间两端的距离、核距离还是未知度距离，距离越大，对Vague值相似性的影响也越大，相似度越小，使之更直观、更符合实际情况。最后通过定理证明以及与相关文献的比较说明该方法具有更好的度量效果。

New method of similarity measure between Vague sets

This paper constructed a new method of similarity measure between Vague sets. Using the method of comparison and Vague theory, presented a new similarity measure formula of Vague sets, which included not only the necessary parameters scaling the similarity of two Vague sets, but also the following problem: for the distance, the one between two ends of Vague values, the score distance or the uncertainty distance, the bigger the size of distance, the larger impact on similarity measure was and the smaller degree of similarity was. The new similarity measure formula was more visual and practical than the fore ones. Finally, by proved theorem and compared to the interrelated literatures, it shows that the method in this paper has the better measure effect.