摘要
分析了现有的5种Vague集(值)之间相似度量的方法,指出这些度量方法不能准确刻画Vague集(值)之间相似度量的本质,导致了错误的推论.通过确定2个Vague值之间精确相似度存在的最小区间,得到一种新的度量方法———最小区间法.该方法不仅具有较好的特征和度量效果,而且为匹配算法的改进提供了数学基础.
This paper analyzed the existing five methods of similarity measures between Vague Sets, and pointed out that these measure methods couldn't describe the nature of similarity measures between Vague Sets, which led to a wrong deduction. Through calculating the minimum interval of the exact grade of similarity between two Vague Elements, a new kind of measure method was proposed that is called the minimal interval approach. It not only has much better characters and measurement effect, but offers a mathematical base for promotion of matching algorithm.
出处
《北方交通大学学报》
CSCD
北大核心
2004年第1期95-99,共5页
Journal of Northern Jiaotong University
基金
国家自然科学基金资助项目(50075002
69674036)
