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Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications

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  • © 2018

Overview

Editors:
  1. Oscar Castillo

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

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  2. Patricia Melin

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

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  3. Janusz Kacprzyk

    1. Systems Research Institute, Polish Academy of Sciences , Warszawa, Poland

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  • Describes recent advances and applications in areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction, and optimization of complex problems
  • Covers theoretical aspects as well as applications, organized into seven main parts
  • Comprises papers on diverse aspects of fuzzy logic, neural networks, and nature-inspired optimization meta-heuristics and their application in various areas

Part of the book series: Studies in Computational Intelligence (SCI, volume 749)

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Table of contents (38 chapters)

  1. Front Matter

    Pages i-xi
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  2. Type-2 Fuzzy Logic in Metaheuristics

    1. Front Matter

      Pages 1-1
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    2. A Comparative Study of Dynamic Adaptation of Parameters in the GWO Algorithm Using Type-1 and Interval Type-2 Fuzzy Logic

      • Luis Rodríguez, Oscar Castillo, Mario García, José Soria
      Pages 3-16

    3. Ensemble Neural Network Optimization Using a Gravitational Search Algorithm with Interval Type-1 and Type-2 Fuzzy Parameter Adaptation in Pattern Recognition Applications

      • Beatriz González, Patricia Melin, Fevrier Valdez, German Prado-Arechiga
      Pages 17-27

    4. Improved Method Based on Type-2 Fuzzy Logic for the Adaptive Harmony Search Algorithm

      • Cinthia Peraza, Fevrier Valdez, Oscar Castillo
      Pages 29-37

    5. Comparison of Bio-Inspired Methods with Parameter Adaptation Through Interval Type-2 Fuzzy Logic

      • Frumen Olivas, Fevrier Valdez, Oscar Castillo
      Pages 39-53

    6. Differential Evolution Algorithm with Interval Type-2 Fuzzy Logic for the Optimization of the Mutation Parameter

      • Patricia Ochoa, Oscar Castillo, José Soria
      Pages 55-65

  3. Neural Networks Theory and Applications

    1. Front Matter

      Pages 67-67
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    2. Person Recognition with Modular Deep Neural Network Using the Iris Biometric Measure

      • Fernando Gaxiola, Patricia Melin, Fevrier Valdez, Juan Ramón Castro
      Pages 69-80

    3. Neuro-evolutionary Neural Network for the Estimation of Melting Point of Ionic Liquids

      • Jorge A. Cerecedo-Cordoba, Juan Javier González Barbosa, J. David Terán-Villanueva, Juan Frausto-Solís
      Pages 81-88

    4. A Proposal to Classify Ways of Walking Patterns Using Spiking Neural Networks

      • Karen Fabiola Mares, Rosario Baltazar, Miguel Ángel Casillas, Víctor Zamudio, Lenin Lemus
      Pages 89-98

    5. Partially-Connected Artificial Neural Networks Developed by Grammatical Evolution for Pattern Recognition Problems

      • Olga Quiroz-Ramírez, Andrés Espinal, Manuel Ornelas-Rodríguez, Alfonso Rojas-Domínguez, Daniela Sánchez, Héctor Puga-Soberanes et al.
      Pages 99-112

  4. Metaheuristics: Theory and Applications

    1. Front Matter

      Pages 113-113
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    2. Bio-inspired Metaheuristics for Hyper-parameter Tuning of Support Vector Machine Classifiers

      • Adán Godínez-Bautista, Luis Carlos Padierna, Alfonso Rojas-Domínguez, Héctor Puga, Martín Carpio
      Pages 115-130

    3. Galactic Swarm Optimization with Adaptation of Parameters Using Fuzzy Logic for the Optimization of Mathematical Functions

      • Emer Bernal, Oscar Castillo, José Soria, Fevrier Valdez
      Pages 131-140

    4. Protein Folding Problem in the Case of Peptides Solved by Hybrid Simulated Annealing Algorithms

      • Anylu Melo-Vega, Juan Frausto-Solís, Guadalupe Castilla-Valdez, Ernesto Liñán-García, Juan Javier González-Barbosa, David Terán-Villanueva
      Pages 141-152

    5. Optimization of the Parameters of Smoothed Particle Hydrodynamics Method, Using Evolutionary Algorithms

      • Juan de Anda-Suárez, Martín Carpio, Solai Jeyakumar, Héctor José Puga-Soberanes, Juan F. Mosiño, Laura Cruz-Reyes
      Pages 153-167

    6. Symbolic Regression by Means of Grammatical Evolution with Estimation Distribution Algorithms as Search Engine

      • M. A. Sotelo-Figueroa, Arturo Hernández-Aguirre, Andrés Espinal, J. A. Soria-Alcaraz, Janet Ortiz-López
      Pages 169-177

  5. Fuzzy Control

    1. Front Matter

      Pages 179-179
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    2. Impact Study of the Footprint of Uncertainty in Control Applications Based on Interval Type-2 Fuzzy Logic Controllers

      • Emanuel Ontiveros, Patricia Melin, Oscar Castillo
      Pages 181-197
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Keywords

About this book

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 problems. The book is organized into seven main parts, each with a collection of papers on a similar subject. The first part presents new concepts and algorithms based on type-2 fuzzy logic for dynamic parameter adaptation in meta-heuristics. The second part discusses network theory and applications, and includes papers describing applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The third part addresses the theory and practice of meta-heuristics in different areas of application, while the fourth part describes diverse fuzzy logic applications in the control area, which can be considered as intelligent controllers. The next two parts explore applications in areas, such as time series prediction, and pattern recognition and new optimization and evolutionary algorithms and their applications respectively. Lastly, the seventh part addresses the design and application of different hybrid intelligent systems.

Reviews

“The book may be useful for scholars trying to identify research topics related to areas such as fuzzy logic, neural networks, and optimization. Many interesting real-world applications greatly enhance the utility of the book. The editors have done a good job of bringing related topics together under various headings.” (S. V. Nagaraj, Computing Reviews, January, 2019)

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Editors and Affiliations

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

    Oscar Castillo

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

    Patricia Melin

  • Systems Research Institute, Polish Academy of Sciences , Warszawa, Poland

    Janusz Kacprzyk

Bibliographic Information

  • Book Title: Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications

  • Editors: Oscar Castillo, Patricia Melin, Janusz Kacprzyk

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-319-71008-2

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing AG 2018

  • Hardcover ISBN: 978-3-319-71007-5Published: 19 January 2018

  • Softcover ISBN: 978-3-319-89028-9Published: 06 June 2019

  • eBook ISBN: 978-3-319-71008-2Published: 10 January 2018

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XI, 546

  • Number of Illustrations: 66 b/w illustrations, 173 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence

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