摘要
针对具有语言评价信息的多指标群聚类分析问题,提出一种基于二元语义信息处理的最大树聚类方法.首先描述了具有语言评价信息的多指标群聚类问题,并介绍了近年来国际上最新发展的二元语义概念及其算子;然后基于二元语义信息处理的方法,将专家给出的语言评价信息进行"量化"集结,并依据传统的最大树聚类分析方法的基本思路,给出了解决基于语言评价信息的最大树聚类方法的计算步骤;最后通过一个算例说明了所提出方法的有效性.
The multiple attribute group clustering analysis problem is described, and the two-tuple linguistic concept and its operator developed in recent years are introduced. A maximal tree clustering analysis method is proposed based on two-tuple linguistic information processing. Based on the approach to two-tuple linguistic processing, linguistic assessment information given by experts is quantified and aggregated, according to the basic ideas of traditional maximal tree clustering method, the calculation steps of the maximal tree clustering method with linguistic assessment information are developed. Finally, a numerical example shows the applicability of the proposed method.
出处
《控制与决策》
EI
CSCD
北大核心
2005年第5期533-536,540,共5页
Control and Decision
基金
国家自然科学基金项目(70371050
70301008)
教育部高等学校优秀青年教师教学科研奖励计划项目(教人司[2002]123)
辽宁省自然科学基金项目(20032028).
关键词
聚类分析
语言评价信息
二元语义
最大树聚类法
群聚类
Decision making
Fuzzy sets
Linguistics
Matrix algebra
Optimal systems
Sensitivity analysis