Abstract
In this paper, we present a novel aggregation method for intuitionistic fuzzy sets (IFS) based on interpolative Boolean algebra (IBA) and logical aggregation (LA). The approach is founded on IFS-IBA calculus, an approach that maintains intuitionistic presumptions when dealing with IFS. The main contribution of IFS-IBA approach is the explicit inclusion of attribute correlation and automated choice of aggregation operator. That is accomplished by introducing parametric Frank t-norm in IFS-IBA calculus and by defining a clear relation between correlation and Frank t-norm parameter. Frank t-norm is chosen since it has the same mathematical properties as a generalized product in IFS-IBA framework. Furthermore, the proposed IFS-IBA LA approach incorporates guidelines for factor normalization, I-fuzzification, logical expression modeling and aggregation. The main applicative benefits of the proposed IFS-IBA LA approach are illustrated in the example of ranking gifted students.
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This study was supported by University of Belgrade - Faculty of Organizational Sciences.
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Milošević, P., Dragović, I., Zukanović, M., Poledica, A., Petrović, B. (2023). IFS-IBA Logical Aggregation with Frank t-norms. In: Massanet, S., Montes, S., Ruiz-Aguilera, D., González-Hidalgo, M. (eds) Fuzzy Logic and Technology, and Aggregation Operators. EUSFLAT AGOP 2023 2023. Lecture Notes in Computer Science, vol 14069. Springer, Cham. https://doi.org/10.1007/978-3-031-39965-7_9
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