摘要
研究了区间直觉正态模糊数(IVINFN)决策信息及其集成算子。首先,定义了区间直觉正态模糊数的概念,提出了运算法则;其次,给出了区间直觉正态模糊数诱导有序加权平均(IVINFN-IOWA)算子和区间直觉正态模糊数诱导有序加权几何(IVINFN-IOWGA)算子的概念,探讨了其性质;在此基础上,分别定义了基于均值和标准差的区间直觉正态模糊数的得分函数和精确函数,给出其排序方法。最后,针对属性值为区间直觉正态模糊数且权重已知的多属性决策问题,给出了其决策方法,并进行了实例分析,结果表明该决策方法是有效的。
Interval-valued intuitionistic normal fuzzy number and its aggregation operators are investigated in this paper. Firstly, interval-valued intuitionistic normal fuzzy number (IVINFN) is defined and its operational laws are proposed. Secondly, IVINFN induced ordered weighted averaging (IVINFN-IOWA) operator and IVINFN induced ordered weighted geometric averaging (IVINFN-IOWGA) are presented. Their pr, operties are discussed. Based on mean and standard deviation, the score function and accurate function of IVINFN are defined, which are used for ranking IVINFNs, Finally, an approach is given to solve the multi-attribute decision making problem in which the information is provided by IVINFNs, and an example is illustrated to show that the proposed method is effective and feasible.
出处
《模糊系统与数学》
CSCD
北大核心
2015年第1期91-100,共10页
Fuzzy Systems and Mathematics
基金
国家自然科学基金资助项目(71371011
71301001
71071002)
安徽省高校省级自然科学研究重点项目(KJ2012A026
KJ2012Z055)
教育部高等学校博士点基金资助项目(20123401110001)
留学回国人员科研启动项目
安徽省自然科学基金资助项目(1308085QG127)
安徽大学研究生创新项目(01001770-10117700024)