Swarm Intelligence
eBook - PDF

Swarm Intelligence

Principles, Advances, and Applications

  1. 210 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Swarm Intelligence

Principles, Advances, and Applications

About this book

Swarm Intelligence: Principles, Advances, and Applications delivers in-depth coverage of bat, artificial fish swarm, firefly, cuckoo search, flower pollination, artificial bee colony, wolf search, and gray wolf optimization algorithms. The book begins with a brief introduction to mathematical optimization, addressing basic concepts related to swarm intelligence, such as randomness, random walks, and chaos theory. The text then:

  • Describes the various swarm intelligence optimization methods, standardizing the variants, hybridizations, and algorithms whenever possible
  • Discusses variants that focus more on binary, discrete, constrained, adaptive, and chaotic versions of the swarm optimizers
  • Depicts real-world applications of the individual optimizers, emphasizing variable selection and fitness function design
  • Details the similarities, differences, weaknesses, and strengths of each swarm optimization method
  • Draws parallels between the operators and searching manners of the different algorithms

Swarm Intelligence: Principles, Advances, and Applications presents a comprehensive treatment of modern swarm intelligence optimization methods, complete with illustrative examples and an extendable MATLAB® package for feature selection in wrapper mode applied on different data sets with benchmarking using different evaluation criteria. The book provides beginners with a solid foundation of swarm intelligence fundamentals, and offers experts valuable insight into new directions and hybridizations.

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Yes, you can access Swarm Intelligence by Aboul Ella Hassanien, Eid Emary in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Science General. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Front Cover
  2. Contents
  3. List of Figures
  4. List of Tables
  5. Preface
  6. 1. Introduction
  7. 2. Bat Algorithm (BA)
  8. 3. Artificial Fish Swarm
  9. 4. Cuckoo Search Algorithm
  10. 5. Firefly Algorithm (FFA)
  11. 6. Flower Pollination Algorithm
  12. 7. Artificial Bee Colony Optimization
  13. 8. Wolf-Based Search Algorithms
  14. 9. Bird's-Eye View
  15. Back Cover