摘要
从信息熵的角度出发,提出了一种新的度量Vague集之间相似度量的计算方法,并对其性质进行讨论。通过与现有方法的比较,阐明该方法具有较强的分辨力。用例子说明Vague集之间相似度量在模式识别中的应用。
A new similarity measure between vague sets based on information entropy has been proposed,and its properties has been discussed.This new method has been illustrated by comparison with the present measure methods that it has stronger discrimination.The similarity measures between vague sets have been applied to pattern recognition.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第25期87-88,132,共3页
Computer Engineering and Applications
基金
陕西省自然科学基金(the Natural Science Foundation of Shaansi Province of China under Grant No.2004A11) 。
关键词
VAGUE集
偏熵
相似度量
vague sets
partial entropy
similarity measures
