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Recent Metaheuristics Algorithms for Parameter Identification

  • Book
  • © 2020

Overview

Authors:
  1. Erik Cuevas

    1. CUCEI, Universidad de Guadalajara, Guadalajara, Mexico

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  2. Jorge Gálvez

    1. CUCEI, Universidad de Guadalajara, Mexico, Mexico

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  3. Omar Avalos

    1. CUCEI, Universidad de Guadalajara, Guadalajara, Mexico

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  • Discusses new, alternative metaheuristic developments that have proved to be effective in various complex problems
  • Introduces novel metaheuristic methods and their practical applications
  • Bridges the gap between recent metaheuristic techniques and interesting identification system methods that benefit from the convenience of metaheuristic schemes

Part of the book series: Studies in Computational Intelligence (SCI, volume 854)

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Table of contents (8 chapters)

  1. Front Matter

    Pages i-xiv
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  2. Introduction to Optimization and Metaheuristic Methods

    • Erik Cuevas, Jorge Gálvez, Omar Avalos
    Pages 1-8

  3. Optimization Techniques in Parameters Setting for Induction Motor

    • Erik Cuevas, Jorge Gálvez, Omar Avalos
    Pages 9-25

  4. An Enhanced Crow Search Algorithm Applied to Energy Approaches

    • Erik Cuevas, Jorge Gálvez, Omar Avalos
    Pages 27-49

  5. Comparison of Solar Cells Parameters Estimation Using Several Optimization Algorithms

    • Erik Cuevas, Jorge Gálvez, Omar Avalos
    Pages 51-95

  6. Gravitational Search Algorithm for Non-linear System Identification Using ANFIS-Hammerstein Approach

    • Erik Cuevas, Jorge Gálvez, Omar Avalos
    Pages 97-134

  7. Fuzzy Logic Based Optimization Algorithm

    • Erik Cuevas, Jorge Gálvez, Omar Avalos
    Pages 135-181

  8. Neighborhood Based Optimization Algorithm

    • Erik Cuevas, Jorge Gálvez, Omar Avalos
    Pages 183-243

  9. Knowledge-Based Optimization Algorithm

    • Erik Cuevas, Jorge Gálvez, Omar Avalos
    Pages 245-277

  10. Back Matter

    Pages 279-297
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Keywords

About this book

This book presents new, alternative metaheuristic developments that have proved to be effective in various complex problems to help researchers, lecturers, engineers, and practitioners solve their own optimization problems. It also bridges the gap between recent metaheuristic techniques and interesting identification system methods that benefit from the convenience of metaheuristic schemes by explaining basic ideas of the proposed applications in ways that can be understood by readers new to these fields. As such it is a valuable resource for energy practitioners who are not researchers in metaheuristics. In addition, it offers members of the metaheuristic community insights into how system identification and energy problems can be translated into optimization tasks.

Authors and Affiliations

  • CUCEI, Universidad de Guadalajara, Guadalajara, Mexico

    Erik Cuevas, Omar Avalos

  • CUCEI, Universidad de Guadalajara, Mexico, Mexico

    Jorge Gálvez

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