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Swarm Intelligence: Principles, Advances, and Applications
Aboul Ella Hassanien
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.
228 pages, 25 black & white illustrations, 43 black & white tables
| Mediji | Grāmatas Hardcover Book (Grāmata ar cieto muguriņu un vāku) |
| Izlaists | 2015. gada 24. novembris |
| ISBN13 | 9781498741064 |
| Izdevēji | Taylor & Francis Inc |
| Lapas | 228 |
| Izmēri | 261 × 186 × 18 mm · 630 g |
| Valoda | Angļu |
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