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基于关联群广义直觉模糊软集的仿真可信度指标聚合方法
引用本文:李晟,彭小奇,彭涛.基于关联群广义直觉模糊软集的仿真可信度指标聚合方法[J].控制与决策,2018,33(1):126-134.
作者姓名:李晟  彭小奇  彭涛
作者单位:中南大学信息科学与工程学院,长沙410083;江西理工大学理学院,江西赣州341000,江西理工大学理学院,江西赣州341000,中南大学信息科学与工程学院,长沙410083
基金项目:国家自然科学基金重大项目(61490702);国家自然科学创新研究群体科学基金项目(61321003).
摘    要:针对仿真可信度主观评估过程存在关联关系时基于独立假设的指标聚合算子失效的问题,以及主观评估时评估专家的判断主观性强且表述能力不足的问题,提出一种基于关联群广义直觉模糊软集的仿真可信度指标聚合方法以及群广义直觉模糊软集关联加权平均聚合算子.结合直觉模糊TOPSIS方法,给出了方法的具体步骤.通过CRH2型高速列车组牵引传动故障注入仿真可信度主观评估实例,验证了所提出方法的可行性和有效性.

关 键 词:仿真可信度  群广义直觉模糊软集  关联聚合算子  可信度指标聚合  CRH2型高速列车组  故障注入仿真

Aggregation method for simulation credibility index based on group generalized intuitionistic fuzzy soft sets with correlations
LI Sheng,PENG Xiao-qi and PENG Tao.Aggregation method for simulation credibility index based on group generalized intuitionistic fuzzy soft sets with correlations[J].Control and Decision,2018,33(1):126-134.
Authors:LI Sheng  PENG Xiao-qi and PENG Tao
Affiliation:School of Information Science and Technology,Central South University,Changsha 410083,China;School of Science,Jiangxi University of Science and Technology,Ganzhou341000,China,School of Information Science and Engineering,Hu''nan First Normal University,Changsha 410205,China and School of Information Science and Technology,Central South University,Changsha 410083,China
Abstract:Aimming at the problems that correlations are widespread during the simulation system credibility evaluation process, which makes the aggregation operators under independent assumption failure and in the simulation credibility subject evaluation process, the expert judgment subjectivity is strong and its language performance ability is insufficient. Therefore, the group general intuitionistic fuzzy soft set correlated weight aggregation(G-GIFSSCWA) operator is defined. Then an aggregation method for the simulation system credibility indicators based on the G-GIFSS with correlations is developed, and a practical example about the China type CRH2 high-speed train fault injection simulation system is given to illustrate the flexibility and effectiveness of the proposed method.
Keywords:
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