A new aggregation method in a fuzzy environment

Abstract

Information aggregation provides a starting point for the ability to make useful inferences from large collections of data, and so it plays an important role in many applications related to the development of intelligent systems. In a fuzzy environment, the existing aggregation operators are generally the t-norm, t-conorm, mean operators, Yager's operator and γ-operator. However, these aggregation operators do not reflect the situation in the aggregation process, i.e., these types of aggregation operators are independent of the aggregation situation. In order to solve these problems, we propose a new aggregation method to reflect the situation in the aggregation process. It is the aggregation based on situation assessment (ASA) method. It consists of the situation assessment model (SAM) and the ASA algorithm. In this ASA method, the SAM is utilized to reflect the situation in the aggregation process. This model generates the parameter, which is controlled by the decision maker. It indicates the current degree of aggregation situation. Therefore, our method can be adapted to certain situations by using the parameter.