摘要
研究Vague集的相似度量的意义及其表示方式,对已有关于Vague集的相似度量进行分析与讨论,探讨了Vague集的相似度量的实质意义和确定相似度量的方法,给出Vague集的相似度量的一种基于距离表示的新方法,同时指出了可以在各种距离意义下产生不同形式的相似度量。另外,做出了把Vague集分解为模糊集的尝试。
In this paper, the meaning of different similarity measures-presented by previous papers are approached, the comparison and analysis among present similarity measure methods in the case of similarity measures between vague values is drawn. And, what similarity measure should be is discussed. Based on the discussion a new form of similarity measure is presented. Besides, the entropy of vague sets is studied, and related discussion is given. In order to study similarity measures of vague sets a method decomposing vague sets into fuzzy sets is presented.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2004年第1期22-26,共5页
Pattern Recognition and Artificial Intelligence
