群体分类偏好下的双重语言信息融合聚类方法  

Clustering method based on dual linguistic information fusion considering group classification preference

作　　者：郝晶晶[1] 朱建军[1] 

机构地区：[1]南京航空航天大学经济与管理学院,南京211106

出　　处：《控制与决策》2015年第6期1044-1052,共9页Control and Decision

基　　金：国家自然科学基金项目(71171112);中央高校基本科研业务费专项资金项目(NS2014086);江苏省高校哲学社会科学重点项目(2012ZDIXM007);广义虚拟经济研究专项资金项目(GX2013-1017(M))

摘　　要：研究一类基于双重信息融合的群体聚类方法.依据偏好信息下专家意见相似关系挖掘群体分类偏好信息考虑专家决策依据向量的相似程度,设计一致性和非一致性测度指标,以表征积重维度下群体聚类的一致及差异度以群体聚类结果差异最小为目标构建规划模型,测算属性权重,并以编网聚类的思想给出聚类结果.算例研究验证了所提出方法的科学性和合理性.A clustering method based on the dual linguistic information fusion is proposed to solve the conflict of clustering results caused by different sorts of information. Specifically, the experts’ similarities are calculated according to preference information, which can be employed to obtain the prior group classification preference. With the similarity vector of decision support information, the consistency and inconsistency indexes are introduced to present the extent of uniformity and difference of group clustering results from dual-dimension calculation. With the objective of minimizing the inconsistency measures of group clustering results, a programming model is constructed to calculate the attribute weights. Furthermore, the netting clustering method is utilized to determine the clustering results. Finally, a case study is conducted to illurstrate the rationality of the proposed method.

关 键 词：双重信息 聚类 语言变量 群体分类偏好 

分 类 号：C943[自然科学总论—系统科学]