Fuzzy classification based on similarity measures between Vague sets

doi:10.3778/j.issn.1002-8331.2010.36.044

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (36): 161-164.DOI: 10.3778/j.issn.1002-8331.2010.36.044

• 数据库、信号与信息处理 • Previous Articles Next Articles

Fuzzy classification based on similarity measures between Vague sets

XU Chang-lin，WEI Li-li

School of Mathematics and Computer Science，Ningxia University，Yinchuan 750021，China

Received:2009-04-17 Revised:2009-06-24 Online:2010-12-21 Published:2010-12-21
Contact: XU Chang-lin

基于Vague集相似度量的模糊分类

许昌林，魏立力

宁夏大学数学计算机学院，银川 750021

通讯作者: 许昌林

Abstract

Abstract: According to the interval-valued fuzzy set theory and the Vague sets theory，a new algorithm based on similarity measures between Vague sets is proposed and applied to the Iris data presented by Fisher.The result shows that more than 95% of the data are classified rightly.The method is simple and efficient，so it is useful for some real problems.

Key words: Vague sets, similarity measure, interval-valued fuzzy set, fuzzy classification

摘要： 在区间值模糊集理论和Vague集理论的基础上，提出了一种新的基于Vague集相似度量的模糊分类方法，对Fisher建立的Iris数据库进行了分类实验处理，分类结果的正确率超过95%。该方法计算简单有效，具有一定的实际应用价值。

关键词: Vague集, 相似度量, 区间值模糊集, 模糊分类

CLC Number:

TP18

XU Chang-lin，WEI Li-li. Fuzzy classification based on similarity measures between Vague sets[J]. Computer Engineering and Applications, 2010, 46(36): 161-164.

许昌林，魏立力. 基于Vague集相似度量的模糊分类[J]. 计算机工程与应用, 2010, 46(36): 161-164.

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Fuzzy classification based on similarity measures between Vague sets

基于Vague集相似度量的模糊分类

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