MADM Method with Interval-Valued Bipolar Uncertain Linguistic Information for Evaluating the Computer Network Security

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.