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...
| Other Authors: | , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Cham
Springer International Publishing
2018, 2018
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| Edition: | 1st ed. 2018 |
| Series: | Studies in Computational Intelligence
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- 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 Networksdeveloped 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