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This work aims to develop a practical study of the uninorms as rule antecedent aggregation operator family in Linguistic Fuzzy Modeling. Although they are well known from a theoretical point of view, they have only recently been introduced in a few specific and recent applications. Uninorms are parameterized operators that combine the membership values in the antecedent in a more flexible way than the classically employed tnorms. Therefore, we carried out an in-depth experimental study with six of them, using 23 regression problems of different size and complexity, and reached some conclusions.

Study on the use of uninorm aggregation operators in linguistic fuzzy modeling