Fuzzy Logic and Neural Networks for Hybrid Intelligent System Design
(Sprache: Englisch)
This book covers recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations. In addition, the above-mentioned methods are applied to areas such as intelligent control and robotics, pattern...
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Klappentext zu „Fuzzy Logic and Neural Networks for Hybrid Intelligent System Design “
This book covers recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations. In addition, the above-mentioned methods are applied to areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. Nowadays, the main topic of the book is highly relevant, as most current intelligent systems and devices in use utilize some form of intelligent feature to enhance their performance. In addition, on the theoretical side, new and advanced models and algorithms of type-2 and type-3 fuzzy logic are presented, which are of great interest to researchers working on these areas. Also, new nature-inspired optimization algorithms and innovative neural models are put forward in the manuscript, which are very popular subjects, at this moment. There are contributions on theoretical aspects as well as applications, which make the book very appealing to a wide audience, ranging from researchers to professors and graduate students.
Inhaltsverzeichnis zu „Fuzzy Logic and Neural Networks for Hybrid Intelligent System Design “
On Decision Making Applications Via Distance Measures.- On Intuitionistic Fuzzy Abstract Algebras.- Generalization of Intuitionistic Fuzzy Submodules of a Module by using Triangular Norms and Conorms and (T, S)-L Subrings.- Fuzzy Dynamic Parameter Adaptation in the Mayfly Algorithm: Implementation of fuzzy adaptation and tests on benchmark functions and Mackey Glass neural network.- Fuzzy classifier using the optimization algorithm by means of particles for the diagnosis of arterial hypertension.- A Survey of Models and Solution Methods for the Internet Shopping Optimization Problem.- A comparison between MFCC and MSE features for text-independent speaker recognition using machine learning algorithms.- Forecasting based on Fuzzy Logic of the Level of Epidemiological Risk for the Mexican State of Tamaulipas.- Bio-Inspired Flower Pollination Algorithm for the Optimization of a Monolithic Neural Network.- Rendezvous and Docking Control of Satellites Using Chaos SynchronizationMethod with Intuitionistic Fuzzy Sliding Mode Control.- Optimizing a convolutional neural network with a hierarchical genetic algorithm for diabetic retinopathy detection.- Interval Type-3 Fuzzy Systems: a natural evolution from type-1 and type-2 fuzzy systems.- A comparative study between bird swarm algorithm and artificial gorilla troops optimize.- Particle Swarm Optimization of Convolutional Neural Networks for Diabetic Retinopathy Classification
Bibliographische Angaben
- 2024, 1st ed. 2023, X, 252 Seiten, 52 farbige Abbildungen, Maße: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Herausgegeben: Oscar Castillo, Patricia Melin
- Verlag: Springer, Berlin
- ISBN-10: 3031220447
- ISBN-13: 9783031220449
Sprache:
Englisch
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