Hierarchical Genetic Algorithm for Type-2 fuzzy Integration applied to Human Recognition
Daniela Sánchez, Patricia Melín · 2013
In this paper a new model of a Hierarchical Genetic Algorithm (HGA) for fuzzy inference system optimization is proposed. The proposed HGA optimizes the fuzzy integrators architecture (type of system, number of trapezoidal membership functions, and their parameters). The model was applied to pattern recognition based on the iris, ear and voice biometrics. Fuzzy logic is used as a method for modular neural networks (MNNs) response integration.