Vague集相似度量  

Similarity Measure of Vague Set

作　　者：朱振国[1,2] 王国胤[2] 

机构地区：[1]重庆交通大学计算机及信息学院,重庆400074 [2]重庆邮电大学计算机科学与技术研究所,重庆400065

出　　处：《计算机科学》2008年第9期220-225,共6页Computer Science

基　　金：国家自然科学基金(No.60573068;No:60373111);重庆市教委科学技术研究项目(040505);新世纪优秀人才支持计划;重庆市自然科学基金重点项目(2005BA2003)

摘　　要：在不确定信息处理中,判定两个知识模式的相似度是知识划分、规则推理的前提。Vague集是处理模糊信息的一种有效工具,众多学者提出了基于Vague集的相似度量方法,但这些方法不足以准确描述Vague集的相似本质,并且度量的准确度较低。本文提出了一种度量Vague集相似度量方法的标准,为研究Vague集相似度量提供了参考;提出了一种新的Vague集相似度量的方法。实验结果表明,本文方法的区分能力高,并且有更好的度量效果。Vague set is a valid tool for processing uncertain information. The similarity measure of two uncertain patterns is important for intelligent reasoning. It is also a key problem to measure the similarity of vague values or vague sets in vague information processing systems. Many methods for similarity measure of vague sets have been proposed in recent years. However, these methods could not precisely describe the essences of the similarity between two vague sets. In this paper,some evaluation criterions for similarity measure of vague set is proposed by analyzing existed similarity measure methods and evaluation criterion. For measuring the similarity of vague sets, a new method is proposed. A new concept named differentiation ability is also developed. Simulation results show that our methods are better than existed methods.

关 键 词：Vague(值)集 相似度量 区分能力 模糊集 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] F270[自动化与计算机技术—控制科学与工程]