Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications
This book comprises papers on diverse aspects of fuzzy logic, neural networks, and nature-inspired optimization meta-heuristics and their application in various areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex...
Συγγραφή απο Οργανισμό/Αρχή: | |
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Άλλοι συγγραφείς: | , , |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Cham :
Springer International Publishing : Imprint: Springer,
2018.
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Έκδοση: | 1st ed. 2018. |
Σειρά: | Studies in Computational Intelligence,
749 |
Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- 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.