Abstract
In this paper, an extension of the Sugeno integral using the operators of the intuitionistic fuzzy sets is presented. The proposed method consists of using the Sugeno integral as an integration method of multiple information sources using the degrees of membership and non-membership through the application of the operators of the intuitionistic fuzzy sets. The proposed method is used to combine the modules output of a modular neural network for face recognition. In this paper, the focus is on aggregation operator that use measures with intuitionistic fuzzy sets, in particular the Sugeno integral. The performance of the proposed method is compared with the traditional Sugeno integral using the Cropped Yale database.
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Martínez, G.E., Melin, P. (2020). Intuitionistic Fuzzy Sugeno Integral for Face Recognition. In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications. Studies in Computational Intelligence, vol 862. Springer, Cham. https://doi.org/10.1007/978-3-030-35445-9_53
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