云模型综合相似度及其语言型多属性决策应用

Comprehensive Similarity of Cloud Model and Its Application in Linguistic Multi-Attribute Decision Making

云模型相似性度量在不确定分类、聚类和决策等领域中具有重要的作用,因此,相似性度量方法的优劣直接影响着云模型的实际应用效果.在分析现有云模型相似性度量方法不足的基础上,构建云模型的模糊格贴近度和形状相似度,并提出一种新的基于正态OWA算子的云模型综合相似性度量方法.该方法从云模型的超熵期望曲线簇角度出发,综合考虑了云模型的位置和形状特征,算例对比分析验证了该方法的科学性和合理性.其次,针对权重信息完全未知,属性指标值为不确定语言变量的多属性决策问题,提出一种基于云模型综合相似度的语言型多属性决策方法.最后,以医药企业新产品开发方案选择实例说明该方法的可行性和有效性.

Cloud model similarity measurement plays an important role in uncertain classification,clustering and decision-making.Therefore,the quality of similarity measurement methods directly affects the application effect of cloud model.Based on the analysis of the shortcomings of existing cloud model similarity measurement methods,the fuzzy lattice closeness and shape similarity of cloud model are constructed,and a new cloud model comprehensive similarity measurement method based on normal OWA operator is proposed.Firstly,from the point of view of the hyper entropy expectation curve cluster of the cloud model,this method comprehensively considers the location and shape characteristics of the cloud model.The comparison between the simulation example and the existing similarity method shows that the method is scientific and reasonable.Secondly,aiming at the multi-attribute decision-making problem with completely unknown weight information and uncertain attribute index value,a linguistic multi-attribute decision-making method based on comprehensive similarity of cloud model is proposed.Finally,the feasibility and effectiveness of this method are illustrated by an example of new product development scheme selection in pharmaceutical enterprises.