Abstract
In this paper, we extend the traditional information aggregating operators to interval-valued bipolar uncertain linguistic sets (IVBULSs) and propose some interval-valued bipolar uncertain linguistic aggregating operators. Then, the good properties of these proposed operators are investigated and these operators are used to solve the interval-valued bipolar uncertain linguistic multiple attribute decision making (MADM) problems. An example for evaluating the computer network security is given to illustrate the proposed methodology.
Highlights
Based on the fuzzy set [1], Atanassov [2], [3] defined the intuitionistic fuzzy set (IFS) with membership degree and non-membership degree
The objective of this work includes: (1) we propose the definition and some operations of interval-valued bipolar uncertain linguistic sets (IVBULSs) on the basis of the bipolar fuzzy sets and uncertain linguistic information processing models; (2) we extend the traditional information aggregating operators to interval-valued bipolar uncertain linguistic sets (IVBULSs) and propose some aggregating operators with interval-valued bipolar uncertain linguistic numbers (IVBULNs); (3) the good properties of these proposed operators are investigated and these operators are used to solve the multiple attribute decision making (MADM) problems with IVBULNs; (4) An example for evaluating the computer network security is given to illustrate the proposed methodology
We use the interval-valued bipolar uncertain linguistic weighted average (IVBULWA) operator to give a procedure to deal with MADM
Summary
Based on the fuzzy set [1], Atanassov [2], [3] defined the intuitionistic fuzzy set (IFS) with membership degree and non-membership degree. How to aggregate the IVBULNs is an interesting topic To solve this problem, we shall propose some novel interval-valued bipolar uncertain linguistic aggregation operators on the basis of the traditional arithmetic and geometric operations. The objective of this work includes: (1) we propose the definition and some operations of interval-valued bipolar uncertain linguistic sets (IVBULSs) on the basis of the bipolar fuzzy sets and uncertain linguistic information processing models; (2) we extend the traditional information aggregating operators to interval-valued bipolar uncertain linguistic sets (IVBULSs) and propose some aggregating operators with interval-valued bipolar uncertain linguistic numbers (IVBULNs); (3) the good properties of these proposed operators are investigated and these operators are used to solve the MADM problems with IVBULNs; (4) An example for evaluating the computer network security is given to illustrate the proposed methodology.
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