计算机工程与应用2011，Vol.47Issue(29)：8-11,4.DOI:10.3778/j.issn.1002-8331.2011.29.003
Vague集的相似度量及其在聚类分析中的应用
Similarity measure of Vague sets and its application in clustering analysis
摘要
Abstract
In the research and development of intelligence system, clustering analysis is a very important problem.A formula for similarity measures based on unknown degree and core between Vague sets is presented.Under the consideration of algo rithm independence and computing complexity,benefiting from the idea of clustering analysis at fuzzy sets,a new direct clus tering algorithm using similarity measure of Vague sets as evaluation criteria is presented.Using the formula, the Vague trans fer closure method and the Vague direct clustering method are used to calculate respectively.The experimental result shows that the direct clustering method based on the similarity of Vague sets is easy,not causing distortion of the original informa tion, and there is no special requirement about the size of the amount of data at the same time.It is more effective than Vague transfer closure method.关键词
Vague集/相似度量/聚类分析/Fuzzy集/直接聚类法Key words
Vague sets/similarity measure/clustering analysis/Fuzzy sets/direct clustering method分类
数理科学引用本文复制引用
王昌,刘娅娅..Vague集的相似度量及其在聚类分析中的应用[J].计算机工程与应用,2011,47(29):8-11,4.基金项目
国家自然科学基金(the National Natural Science Foundation of China under Grant No.11171271,No.11001217) （the National Natural Science Foundation of China under Grant No.11171271,No.11001217）
西北大学研究生自主创新基金项目(No.10YZZ05). （No.10YZZ05）
