Generalized Fuzzy Operators

Information aggregation is one of the key issues in development of intelligent systems. Although fuzzy set theory provides a host of attractive aggregation operators for integrating the membership values representing uncertain information, the results do not always follow the modeled real phenomena. Researches on this area have shown that better results can be reached by using various aggregation operation families. In this paper some new approaches towards the generalizations of the conventional triangular norms are summarized. It is shown that by omitting and/or modifying some axioms in the axiom skeleton new generalized operation families can be obtained. The paper summarizes some new operations, including novel parametric generalized operations, absorbing-norms and distance-based operators.