Swarm Intelligence Algorithms (eBook, ePUB)

A Tutorial
Redaktion: Slowik, Adam

• Format: ePub

Produktbeschreibung

This book can provide the basics for understanding how swarm intelligence algorithms work, and aid readers in programming these algorithms to solve various computational problems. It is useful for students studying nature-based optimization algorithms, and can be a helpful for learning the basics of these algorithms efficiently.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 362
• Erscheinungstermin: 25. August 2020
• Englisch
• ISBN-13: 9780429749490
• Artikelnr.: 62173013

Autorenporträt

Adam Slowik (IEEE Member 2007; IEEE Senior Member 2012) is an Associate Professor in the Department of Electronics and Computer Science, Koszalin University of Technology. His research interests include soft computing, computational intelligence, and, particularly, bio-inspired optimization algorithms and their engineering applications. He was a recipient of one Best Paper Award (IEEE Conference on Human System Interaction - HSI 2008).

Inhaltsangabe

1. Ant Colony Optimization. 2. Arti
cial Bee Colony Algorithm. 3. Bacterial Foraging Optimization. 4. Bat Algorithm. 5. Cat Swarm Optimization. 6. Chicken Swarm Optimization. 7. Cockroach Swarm Optimization. 8. Crow Search Algorithm. 9. Cuckoo Search Algorithm. 10. Dynamic Virtual Bats Algorithm. 11. Dispersive Flies Optimisation: A Tutorial. 12. Elephant Herding Optimization. 13. Fire
y Algorithm. 14. Glowworm Swarm Optimization - A Tutorial. 15. Grasshopper Optimization Algorithm. 16. Grey Wolf Optimizer. 17. Hunting Search Algorithm. 18. Krill Herd Algorithm. 19. Monarch Butter
y Optimization. 20. Particle Swarm Optimization. 21. Salp Swarm Optimization: Tutorial. 22. Social Spider Optimization. 23. Stochastic Diffusion Search: A Tutorial. 24. Whale Optimization Algorithm.