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Fuzzy Logic and Neural Networks for Hybrid Intelligent System Design

  • Book
  • © 2023

Overview

Editors:
  1. Oscar Castillo

    1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Mexico

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    You can also search for this editor in PubMed   Google Scholar

  2. Patricia Melin

    1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Mexico

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • Covers recent developments on fuzzy logic, neural networks, and optimization algorithms
  • Includes applications to intelligent control, robotics, pattern recognition, medical diagnosis, and time series
  • Presents new and advanced models and algorithms of type-2 and type-3 fuzzy logic

Part of the book series: Studies in Computational Intelligence (SCI, volume 1061)

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Table of contents (14 chapters)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. On Decision Making Applications via Distance Measures

    • Feride Tuğrul, Mehmet Çitil
    Pages 1-21

  3. On Intuitionistic Fuzzy Abstract Algebras

    • Gökhan Çuvalcıoğlu, Sinem Tarsuslu
    Pages 23-49

  4. Generalization of Intuitionistic Fuzzy Submodules of a Module by Using Triangular Norms and Conorms and (T,S)-L Subrings

    • Ümit Deniz
    Pages 51-67

  5. Fuzzy Dynamic Parameter Adaptation in the Mayfly Algorithm: Implementation of Fuzzy Adaptation and Tests on Benchmark Functions and Neural Networks

    • Enrique Lizarraga, Fevrier Valdez, Oscar Castillo, Patricia Melin
    Pages 69-84

  6. Fuzzy Classifier Using the Particle Swarm Optimization Algorithm for the Diagnosis of Arterial Hypertension

    • Martha Pulido, Patricia Melin
    Pages 85-103

  7. A Survey of Models and Solution Methods for the Internet Shopping Optimization Problem

    • Miguel Ángel García Morales, Hector Joaquín Fraire Huacuja, Juan Frausto Solís, Laura Cruz Reyes, Claudia Guadalupe Gómez Santillán
    Pages 105-122

  8. A Comparison Between MFCC and MSE Features for Text-Independent Speaker Recognition Using Machine Learning Algorithms

    • Joseph Isaac Ramírez-Hernández, Alain Manzo-Martínez, Fernando Gaxiola, Luis C. González-Gurrola, Vania C. Álvarez-Oliva, Roberto López-Santillán
    Pages 123-140

  9. Forecasting Based on Fuzzy Logic of the Level of Epidemiological Risk for the Mexican State of Tamaulipas

    • Paula Hernández-Hernández, Norberto Castillo-García
    Pages 141-153

  10. Bio-inspired Flower Pollination Algorithm for the Optimization of a Monolithic Neural Network

    • Hector Carreon-Ortiz, Patricia Melin, Fevrier Valdez
    Pages 155-176

  11. Rendezvous and Docking Control of Satellites Using Chaos Synchronization Method with Intuitionistic Fuzzy Sliding Mode Control

    • Onur Silahtar, Fatih Kutlu, Özkan Atan, Oscar Castillo
    Pages 177-197

  12. Optimizing a Convolutional Neural Network with a Hierarchical Genetic Algorithm for Diabetic Retinopathy Detection

    • Rodrigo Cordero-Martínez, Daniela Sánchez, Patricia Melin
    Pages 199-208

  13. Interval Type-3 Fuzzy Systems: A Natural Evolution from Type-1 and Type-2 Fuzzy Systems

    • Oscar Castillo, Juan R. Castro, Patricia Melin
    Pages 209-221

  14. A Comparative Study Between Bird Swarm Algorithm and Artificial Gorilla Troops Optimizer

    • Ivette Miramontes, Patricia Melin
    Pages 223-236

  15. Particle Swarm Optimization of Convolutional Neural Networks for Diabetic Retinopathy Classification

    • Patricia Melin, Daniela Sánchez, Rodrigo Cordero-Martínez
    Pages 237-252
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Keywords

About this book

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.

Editors and Affiliations

  • Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Mexico

    Oscar Castillo, Patricia Melin

Bibliographic Information

  • Book Title: Fuzzy Logic and Neural Networks for Hybrid Intelligent System Design

  • Editors: Oscar Castillo, Patricia Melin

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-031-22042-5

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023

  • Hardcover ISBN: 978-3-031-22041-8Published: 28 January 2023

  • Softcover ISBN: 978-3-031-22044-9Published: 28 January 2024

  • eBook ISBN: 978-3-031-22042-5Published: 27 January 2023

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: X, 252

  • Number of Illustrations: 30 b/w illustrations, 52 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence

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