An improved model in fusing multi-source information based on Z-numbers and POWA operator

Information of the real world is often imperfect and partially reliable. Thus, processing the uncertain information is of great importance. Z-number, proposed by Zadeh, is an effective tool to describe the real-world information, which contains both fuzziness and reliability of information. In most decision-making problems, information is usually provided by experts. However, opinions among experts may be conflicting. How to deal with the opinions of multiple experts from an objective point of view, especially when there is a conflict among the opinions of multiple experts, is still an open issue. Therefore, in this paper, an improved model in fusing multi-source information based on Z-numbers and power ordered weighted average (POWA) operator is proposed, considering both the decision makers’ attitude characteristics and the support degree among evidence. The soft likelihood function based on Z-numbers is included in the improved model. A case study in medical diagnosis and some other examples of scenario simulation are used to illustrate the validity and superiority of the proposed model.