摘要
讨论模糊模式识别中模糊集之间的相似度量.针对模糊集的推广形式——Vague集,给出Vague集之间一系列新的相似度量方法,并对其性质进行讨论.通过与现有方法的比较,阐明该方法有较强的分辨能力.对连续论域的情况一并作了讨论,给出相应度量的积分表示.最后,用例子说明Vague集之间的相似度量在模式识别中的应用.
The problem of similarity measure between fuzzy sets in pattern recognition is discussed. A set of newmethods for measuring the degree of similarity between vague sets as a generation of Zadeh's fuzzy sets is proposedand their properties are discussed. These new methods are illustrated by comparison with the present measure methodsthat they have stronger discrimination. Furthermore, a set of corresponding methods for measuring the degree ofsimilarity between vague sets in a continuous universe is given. Finally, the similarity measures between vaguesets are applied to pattern recognition.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2004年第2期141-145,共5页
Pattern Recognition and Artificial Intelligence
基金
山东省自然科学基金(No.Y2001G07)
关键词
模糊集
VAGUE集
直觉模糊集
相似度量
模式识别
Fuzzy Sets
Vague Sets
Intuitionistic Fuzzy Sets
Similarity Measures
Pattern Recognition