Vague集相似度量及其在模式识别中的应用

Similarity Measures between Vague Sets and Their Application to Pattern Recognition

Vague集自提出以来,由于它在各个领域中的广泛应用而引起众多学者的注意,而相似度量是其中的关键技术.目前虽有多种相似度量的方法被提出,但还没有一个相应的相似度量约束条件标准.在Li(2003)的相关工作之上提出一种改进的Vague集相似度量公理化定义,指出一个相似度量必须满足的约束条件,然后引入两种新Vague集相似度量方法,并证明它们满足这些公理化条件,最后给出一个它们在模式识别的应用实例.

Since Vague set was proposed,it has gained great attention from researchers for its applications in various fields. Similarity measure is one of the most important technologies in vague set. Though some similarity measures have been proposed, there isn't a responding criterion. An axiom definition of similarity measure based on Li's related works, which constrains the necessary conditions of a similarity measure, is proposed. Then two new methods are introduced,and proved to satisfy the axiom defined above. Finally, an example of their application to pattern recognition is given.