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Fuzzy Logic Augmentation of Nature-Inspired Optimization Metaheuristics

Theory and Applications

  • Book
  • © 2015

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

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • Describes recent advances on fuzzy logic augmentation of nature-inspired optimization metaheuristics
  • Includes various application in areas such as intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems
  • The book is organized in two main parts focusing on theoretical aspects of fuzzy logic augmentation of nature-inspired optimization metaheuristics (part 1) , as well as application of optimization algorithms (part 2)
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Computational Intelligence (SCI, volume 574)

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Table of contents (12 chapters)

  1. Front Matter

    Pages i-viii
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  2. Theory

    1. Front Matter

      Pages 1-1
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    2. Fuzzy Logic for Dynamic Parameter Tuning in ACO and Its Application in Optimal Fuzzy Logic Controller Design

      • Héctor Neyoy, Oscar Castillo, José Soria
      Pages 3-28

    3. Fuzzy Classification System Design Using PSO with Dynamic Parameter Adaptation Through Fuzzy Logic

      • Frumen Olivas, Fevrier Valdez, Oscar Castillo
      Pages 29-47

    4. Differential Evolution with Dynamic Adaptation of Parameters for the Optimization of Fuzzy Controllers

      • Patricia Ochoa, Oscar Castillo, José Soria
      Pages 49-63

    5. A New Bat Algorithm with Fuzzy Logic for Dynamical Parameter Adaptation and Its Applicability to Fuzzy Control Design

      • Jonathan Pérez, Fevrier Valdez, Oscar Castillo
      Pages 65-79

    6. Optimization of Benchmark Mathematical Functions Using the Firefly Algorithm with Dynamic Parameters

      • Cinthya Solano-Aragón, Oscar Castillo
      Pages 81-89

    7. Cuckoo Search via Lévy Flights and a Comparison with Genetic Algorithms

      • Maribel Guerrero, Oscar Castillo, Mario García
      Pages 91-103

    8. A Harmony Search Algorithm Comparison with Genetic Algorithms

      • Cinthia Peraza, Fevrier Valdez, Oscar Castillo
      Pages 105-123

  3. Applications

    1. Front Matter

      Pages 125-125
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    2. A Gravitational Search Algorithm for Optimization of Modular Neural Networks in Pattern Recognition

      • Beatriz González, Fevrier Valdez, Patricia Melin, German Prado-Arechiga
      Pages 127-137

    3. Ensemble Neural Network Optimization Using the Particle Swarm Algorithm with Type-1 and Type-2 Fuzzy Integration for Time Series Prediction

      • Martha Pulido, Patricia Melin
      Pages 139-149

    4. Clustering Bin Packing Instances for Generating a Minimal Set of Heuristics by Using Grammatical Evolution

      • Marco Aurelio Sotelo-Figueroa, Héctor José Puga Soberanes, Juan Martín Carpio, Héctor J. Fraire Huacuja, Laura Cruz Reyes, Jorge Alberto Soria Alcaraz
      Pages 151-162

    5. Comparative Study of Particle Swarm Optimization Variants in Complex Mathematics Functions

      • Juan Carlos Vazquez, Fevrier Valdez, Patricia Melin
      Pages 163-178

    6. Optimization of Modular Network Architectures with a New Evolutionary Method Using a Fuzzy Combination of Particle Swarm Optimization and Genetic Algorithms

      • Fevrier Valdez
      Pages 179-195
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Keywords

About this book

This book describes recent advances on fuzzy logic augmentation of nature-inspired optimization metaheuristics and their application in areas such as intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. The book is organized in two main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of theoretical aspects of fuzzy logic augmentation of nature-inspired optimization metaheuristics, which basically consists of papers that propose new optimization algorithms enhanced using fuzzy systems. The second part contains papers with the main theme of application of optimization algorithms, which are basically papers using nature-inspired techniques to achieve optimization of complex optimization problems in diverse areas of application.

Reviews

From the book reviews:

“This book presents recent developments in a specific area of computational intelligence, namely fuzzy logic augmentation of nature-inspired optimization metaheuristics and their applications. … the book is very interesting for those working in the field of computational intelligence. It will be useful for the researchers and practitioners working in this area of research.” (Petrica Pop, Computing Reviews, February, 2015)

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 Augmentation of Nature-Inspired Optimization Metaheuristics

  • Book Subtitle: Theory and Applications

  • Editors: Oscar Castillo, Patricia Melin

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-319-10960-2

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing Switzerland 2015

  • Hardcover ISBN: 978-3-319-10959-6Published: 01 October 2014

  • Softcover ISBN: 978-3-319-38546-4Published: 10 September 2016

  • eBook ISBN: 978-3-319-10960-2Published: 20 September 2014

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: VIII, 195

  • Number of Illustrations: 98 b/w illustrations

  • Topics: Computational Intelligence, Artificial Intelligence

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