HOW TO DESIGN OPTIMIZATION ALGORITHMS BY APPLYING NATURAL BEHAVIORAL PATTERNS.
How to Design Optimization Algorithms by Applying Natural Behavioral Patterns is a guide book that introduces readers to optimization algorithms based on natural language processing. Readers will learn about the basic concept of optimization, optimization algorithm fundamentals and the methods emplo...
| Kaituhi matua: | |
|---|---|
| Ētahi atu kaituhi: | |
| Hōputu: | Licensed eBooks |
| Reo: | Ingarihi |
| I whakaputaina: |
[S.l.] :
BENTHAM SCIENCE PUBLISHER,
2021.
|
| Urunga tuihono: | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=3050793 |
Rārangi ihirangi:
- Intro
- CONTENTS
- Cover
- Title
- Copyright
- End User License Agreement
- Contents
- Foreword
- Preface
- Dedication
- Introduction to Optimization
- Nature and Optimization Algorithms
- How to Formulate Natural Ideas in Several Algorithms
- 3.1. SSPCO ALGORITHM (SEE-SEE PARTRIDGE)
- 3.2. SIMULATION RESULTS
- 3.3. CHAOTIC SSPCO ALGORITHM
- 3.4. THE FIRST METHOD: CHAOTIC SSPCO ALGORITHM
- 3.5. THE SECOND EQUATION: CHAOTIC SSPCO
- 3.6. SIMULATION AND RESULTS
- 3.7. DATA CLUSTERING USING BY CHAOTIC SSPCO ALGORITHM
- 3.8. FITNESS FUNCTION
- 3.9. EXPERIMENTAL STUDY
- 3.10. RESULTS AND DISCUSSIONS
- 3.11. T-TEST
- 3.12. FRIEDMAN TEST
- 3.13. A CLUSTERING APPROACH BY SSPCO OPTIMIZATION ALGORITHM BASED ON CHAOTIC INITIAL POPULATION
- 3.14. FITNESS FUNCTION
- 3.15. EXPERIMENTAL STUDY
- 3.16. RESULTS AND DISCUSSIONS
- 3.17. T-TEST
- 3.18. TRAVELING SALESMAN PROBLEM
- 3.19. SIMULATION AND RESULTS
- 3.20. ESCAPE FROM HUNTER PARTICLE SWARM OPTIMIZATION
- 3.21. EXPERIMENTAL RESULT
- 3.22. PROVIDING A BIRD ALGORITHM BASED ON CLASSICAL CONDITIONING LEARNING BEHAVIOUR
- 3.23. SIMULATION AND RESULTS
- How to Transform the Behaviour in Nature into the Algorithm
- 4.1. CHAOTIC INTIAL POPULATION
- 4.2. CHAOTIC CREATION OF FOOD SOURCES
- Conclusion
- References
- REFERENCES
- Subject Index
- Back Cover