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CABOSFV算法中集合稀疏差异度阈值确定方法
引用本文:宋艳,肖乾. CABOSFV算法中集合稀疏差异度阈值确定方法[J]. 舰船科学技术, 2006, 28(1): 99-102
作者姓名:宋艳  肖乾
作者单位:哈尔滨工程大学,经济管理学院,黑龙江,哈尔滨,150001;中国船舶重工集团公司,北京,100861
摘    要:在实际应用中,CABOSFV算法初始参数———集合稀疏差异度阈值b的确定是否合理,对聚类结果是否有效起决定作用。本文针对如何科学方便地确定集合稀疏差异度阈值b进行了深入研究,给出了集合稀疏差异度阈值确定方法,并通过该方法进行了实例计算。计算结果表明,由于该方法能够确定聚类结果中类的对象组成最小数量,聚类结果的粗糙与精细程度可以人为控制,对聚类结果的准确及高效提供了很好的保证,能够为CABOSFV算法进行聚类提供合理的阈值。

关 键 词:聚类  CABOSFV算法  集合稀疏差异度  阈值
文章编号:1672-7649(2006)01-0099-04
收稿时间:2005-11-10
修稿时间:2005-11-10

The method of how to determine threshold value of set-square-difference in CABOSFV algorithm
SONG Yan,XIAO Qian. The method of how to determine threshold value of set-square-difference in CABOSFV algorithm[J]. Ship Science and Technology, 2006, 28(1): 99-102
Authors:SONG Yan  XIAO Qian
Affiliation:1. Economics and Management School, Harbin Engineering University,Harbin 150001, China; 2. China Shipbuilding Industry Cooperation,Beijing 100861 ,China
Abstract:Using CABOFSV to cluster,whether b,the beginning parameter,threshold value of set-square-difference,also named up-bound of a cluster,is reasonable or not is fatal to clustering results.In this paper,how to determine the threshold value of set-square-difference in CABOSFV algorithm is deeply studied.Then,the method of how to determine threshold value of set-square-difference is put forward and is expressed by a formula,and a group of data is calculated by this method.The calculating results indicate that this threshold is reasonable for CABOSFV because clustering results are controlled by people and ensured correctly and effectively for this method can fix the least number of objects in one cluster.
Keywords:cluster  CABOSFV algorithm  set-square-difference  threshold
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