Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applica
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- Artikel-Nr.: 10462561
Beschreibung
Part I: Type-2 Fuzzy Logic in Metaheuristics.- A comparative study of dynamic adaptation of parameters in the GWO algorithm using type-1 and interval type-2 fuzzy logic.- Ensemble Neural Network optimization using a gravitational search algorithm with Interval Type-1 and Type-2 fuzzy parameter adaptation in pattern recognition applications.- Improved method based on type-2 fuzzy logic for the adaptive harmony search algorithm.- Comparison of bio-inspired methods with parameter adaptation through interval type-2 fuzzy logic.- Differential Evolution algorithm with Interval type-2 fuzzy logic for the optimization of the mutation parameter.- Part II: Neural Networks Theory and Applications.- Person recognition with modular deep neural network using the iris biometric measure.- Neuro-evolutionary Neural Network for the Estimation of Melting Point of Ionic Liquids.- A proposal to classify ways of walking patterns using spik-ing neural networks.- Partially-connected Artificial Neural Networks developed by Grammatical Evolution for pattern recognition problems.- Part III: Metaheuristics: Theory and Applications.- Bio-inspired Metaheuristics for Hyper-parameter Tuning of Support Vector Machine Classifiers.
Eigenschaften
Breite: | 161 |
Gewicht: | 994 g |
Höhe: | 242 |
Länge: | 37 |
Seiten: | 546 |
Sprachen: | Englisch |
Autor: | Janusz Kacprzyk, Oscar Castillo, Patricia Melin |
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