Swarm Intelligence Algorithms (Two Volume Set)

2. Auflage 2027
ISBN: 978-1-041-36805-2
Verlag: Taylor & Francis

Buch, Englisch, 1056 Seiten, Format (B × H): 156 mm x 234 mm

In this book, the several most recent algorithms in the area of swarm intelligence algorithms are presented. The book contains the most compact description of 36 swarm intelligence algorithms. Each chapter is written by the world-recognized researchers which possess a high experience in the area of given swarm intelligence algorithm or even they are an author of a given swarm intelligence algorithm. The chapter authors in their scientific activity are working with given algorithm, thus they can guarantee a high scientific quality for each chapter. In each chapter, the main focus is on recent modifications of the presented algorithm, and with his applications to solving real-world problems.

- Learn modern swarm intelligence optimization algorithms

- Learn different modifications of swarm intelligence algorithms

- Learn how to apply swarm intelligence algorithms to real-world problems

- Show different case studies on real-world application of swarm intelligence algorithms

- Learn how the selected algorithm works

Zielgruppe

General

Autoren/Hrsg.

Slowik, Adam

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
• Mathematik | Informatik EDV | Informatik Technische Informatik
• Mathematik | Informatik Mathematik Algebra Zahlentheorie

Inhaltsverzeichnis

1. Ant Colony Optimization – Modifications and Applications 2. Artificial Bee Colony Algorithm – Modifications and Applications 3. Bacterial Foraging Optimization – Modifications and Applications 4. Bat Algorithm – Modifications and Applications 5. Cat Swarm Optimization – Modifications and Applications 6. Chicken Swarm Optimization – Modifications and Applications 7. Cockroach Swarm Optimization – Modifications and Applications 8. Crow Search Algorithm – Modifications and Applications 9. Cuckoo Search Algorithm – Modifications and Applications 10. Dynamic Virtual Bats Algorithm – Modifications and Applications 11. Dispersive Flies Optimization – Modifications and Applications 12. Elephant Herding Optimization – Modifications and Applications 13. Firefly Algorithm – Modifications and Applications 14. Glow Swarm Optimization – Modifications and Applications 15. Grasshopper Optimization Algorithm – Modifications and Applications 16. Grey Wolf Optimizer – Modifications and Applications 17. Hunting Search Algorithm – Modifications and Applications 18. Krill Herd Algorithm – Modifications and Applications 19. Monarch Butterfly Optimization – Modifications and Applications 20. Particle Swarm Optimization – Modifications and Applications 21. Salp Swarm Algorithm – Modifications and Applications 22. Social Spider Optimization – Modifications and Applications 23. Stochastic Diffusion Search – Modifications and Applications 24. Whale Optimization Algorithm – Modifications and Applications 25. Crayfish Optimization Algorithm – Modifications and Applications 26. Remora Optimization Algorithm – Modifications and Applications 27. Puma Optimizer – Modifications and Applications 28. Tuna Swarm Optimization – Modifications and Applications 29. Artificial Locust Swarm Optimization Algorithm – Modifications and Applications 30. Dwarf Mongoose Optimization – Modifications and Applications 31. Artificial Lemming Algorithm – Modifications and Applications 32. Griffon Vultures Optimization Algorithm – Modifications and Applications 33. Tunicate Swarm Algorithm – Modifications and Applications 34. Jellyfish Search Optimizer – Modifications and Applications 35. Goose Algorithm – Modifications and Applications 36. Sparrow Search Algorithm – Modifications and Applications

Über Autor(innen)

ADAM SLOWIK (IEEE Member 2007; IEEE Senior Member 2012) received the B.Sc. and M.Sc. degrees in computer engineering and electronics in 2001 and the Ph.D. degree with distinction in 2007 from the Department of Electronics and Computer Science, Koszalin University of Technology, Koszalin, Poland. He received the Dr. habil. degree in computer science (intelligent systems) in 2013 from the Department of Mechanical Engineering and Computer Science, Czestochowa University of Technology, Czestochowa, Poland. Since October 2013, he has been an Associate Professor in the Department of Electronics and Computer Science, Koszalin University of Technology. His research interests include soft computing, machine learning, neural networks, fuzzy systems, computational intelligence, bio-inspired optimization algorithms, and their engineering applications. He is a Reviewer for many international scientific journals and many international conferences. He is an author or coauthor of over 200 refereed articles in international journals, 2 books, and co-editor of conference proceedings and books, including two invited talks. Dr. Slowik was an Associate Editor of the IEEE Transactions on Industrial Electronics (2009-2011). He is an Associate Editor for the IEEE Transactions on Fuzzy Systems, IEEE Transactions on Cybernetics, and the IEEE Transactions on Industrial Informatics. Dr. Slowik was the Head of the Department of Computer Engineering, Koszalin University of Technology (2019-2021). He is a member of the program committees of several important international conferences in the area of machine learning, artificial intelligence, and evolutionary computation. He was a recipient of one Best Paper Award (IEEE Conference on Human System Interaction - HSI 2008). In 2022-2026, he was on the list of Top 2% Scientists Worldwide by Stanford University. Dr. Slowik has often organized special sessions in such journals as IEEE Transactions on Industrial Electronics, IEEE Transactions on Industrial Informatics, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Consumer Electronics, and Neural Computing and Applications.