Title :
Hierarchical Genetic Algorithm for Type-2 fuzzy Integration applied to Human Recognition
Author :
Sanchez, Dominick ; Melin, Patricia
Author_Institution :
Tijuana Inst. Technol., Tijuana, Mexico
Abstract :
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.
Keywords :
fuzzy logic; fuzzy reasoning; fuzzy set theory; genetic algorithms; iris recognition; neural nets; optimisation; speech recognition; HGA; MNN response integration; ear biometrics; fuzzy inference system optimization; fuzzy integrators architecture; fuzzy logic; hierarchical genetic algorithm; human recognition; iris biometrics; modular neural networks response integration; pattern recognition; type-2 fuzzy integration; voice biometrics; Ear; Genetic algorithms; Image recognition; Iris recognition; Neural networks; Training; Granular computing; Hierarchical Genetic Algorithms; Modular Neural Networks; Optimization; Type-2 Fuzzy Logic;
Conference_Titel :
IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), 2013 Joint
Conference_Location :
Edmonton, AB
DOI :
10.1109/IFSA-NAFIPS.2013.6608416
