Nature-inspired computing : physics- and chemistry-based algorithms /
| Main Authors: | , |
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| Corporate Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
Boca Raton, FL :
CRC Press,
[2017]
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- Cover ; Half Title ; Title Page ; Copyright page ; Contents ; Foreword ; Preface ; Acknowledgments ; Authors ; Chapter 1: Dialectics of Nature: Inspiration for Computing ; 1.1 Inspiration from Nature ; 1.2 Brief History of Natural Sciences ; 1.2.1 Laws of Motion.
- 1.2.2 Law of Gravitation 1.2.3 Transformation between Heat and Mechanical Energy ; 1.2.4 Transformation between Mass and Energy ; 1.2.5 Light and Optics ; 1.2.6 Sound and Acoustics ; 1.2.7 Hydrology and Dynamics ; 1.2.8 Development in Chemistry.
- 1.2.9 Development in Biological Sciences 1.3 Traditional Approaches to Search and Optimization ; 1.3.1 Line Search ; 1.3.2 Golden Section Search ; 1.3.3 Fibonacci Search ; 1.3.4 Newton's Method ; 1.3.5 Secant Method ; 1.3.6 Gradient-Based Methods ; 1.3.6.1 Descent Methods.
- 1.3.6.2 Gradient Methods 1.3.6.3 Steepest Descent Method (or Gradient Descent) ; 1.3.7 Classical Newton's Method ; 1.3.8 Modified Newton's Method ; 1.3.9 Levenberg-Marquardt Modification ; 1.3.10 Quasi-Newton Method ; 1.3.11 Conjugate Direction Methods.
- 1.3.12 Conjugate Gradient Methods 1.3.13 BFGS Method ; 1.3.14 Deterministic vs Stochastic Algorithms ; 1.3.15 Local Search Methods ; 1.3.15.1 Scatter Search ; 1.3.15.2 Tabu Search (TS) ; 1.3.15.3 Random Search (RS) ; 1.3.15.4 Downhill Simplex (Nelder-Mead) Method.