Nature-Inspired Optimization Algorithms
Autor Xin She Yangen Limba Engleză Paperback – 13 sep 2020
- Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature
- Provides a theoretical understanding and practical implementation hints
- Presents a step-by-step introduction to each algorithm
- Includes four new chapters covering mathematical foundations, techniques for solving discrete and combination optimization problems, data mining techniques and their links to optimization algorithms, and the latest deep learning techniques, background and various applications
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Specificații
ISBN-13: 9780128219867
ISBN-10: 0128219866
Pagini: 310
Dimensiuni: 191 x 235 mm
Greutate: 0.54 kg
Ediția:2
Editura: ELSEVIER SCIENCE
ISBN-10: 0128219866
Pagini: 310
Dimensiuni: 191 x 235 mm
Greutate: 0.54 kg
Ediția:2
Editura: ELSEVIER SCIENCE
Cuprins
1. Introduction to Algorithms 2. Mathematical Foundations3. Analysis of Algorithms4. Random Walks and Optimization5. Simulated Annealing6. Genetic Algorithms7. Differential Evolution8. Particle Swarm Optimization9. Firefly Algorithms10. Cuckoo Search11. Bat Algorithms12. Flower Pollination Algorithms13. A Framework for Self-Tuning Algorithms14. How to Deal With Constraints15. Multi-Objective Optimization16. Data Mining and Deep LearningAppendix A Test Function Benchmarks for Global OptimizationAppendix B Matlab® Programs
Recenzii
"...the book is well written and easy to follow, even for algorithmic and mathematical laymen. Since the book focuses on optimization algorithms, it covers a very important and actual topic." --IEEE Communications Magazine, Nature-Inspired Optimization Algorithms
"...this book strives to introduce the latest developments regarding all major nature-inspired algorithms…" - HPCMagazine.com, August 2014
"...this book strives to introduce the latest developments regarding all major nature-inspired algorithms…" - HPCMagazine.com, August 2014