
Nature-Inspired Computation and Swarm Intelligence
Algorithms, Theory and Applications
Description
Key Features
- Introduces nature-inspired algorithms and their fundamentals, including: particle swarm optimization, bat algorithm, cuckoo search, firefly algorithm, flower pollination algorithm, differential evolution and genetic algorithms as well as multi-objective optimization algorithms and others
- Provides a theoretical foundation and analyses of algorithms, including: statistical theory and Markov chain theory on the convergence and stability of algorithms, dynamical system theory, benchmarking of optimization, no-free-lunch theorems, and a generalized mathematical framework
- Includes a diversity of case studies of real-world applications: feature selection, clustering and classification, tuning of restricted Boltzmann machines, travelling salesman problem, classification of white blood cells, music generation by artificial intelligence, swarm robots, neural networks, engineering designs and others
Readership
Researchers, advanced undergraduate and graduate students in computer science, engineering, optimization, data science, and management science
Table of Contents
1. Nature-Inspired Computation and Swarm Intelligence
2. Bat Algorithm and Cuckoo Search Algorithms
3. Firefly Algorithm and Flower Pollination Algorithm
4. Bio-inspired Algorithms: Principles, Implementation and Applications to wireless communicatinonPart II: Theory and Analysis
5. Mathematical Foundations for Algorithm Analysis
6. Probability Theory for Analysing Nature-Inspired Algorithms
7. Theoretical Framework for Algorithm AnalysisPart III: Applications
8. Tuning Restricted Boltzmann Machines
9. Traveling Salesman Problem: Review and New Results
10. Clustering with Nature Inspired Metaheuristics
11. Bat Algorithm for Feature Selection and White Blood Cell Classification
12. Modular Granular Neural Networks Optimisation using the Firefly Algorithm applied to Time Series Prediction
13. Artificail Intelligence Methods for Music generation: A review and future perspectives
14. Optimized controller design for island microgrid employing non-dominated sorting firefly Algorithm (NSFA)
15. Swarm Robotics: A case study -- Bat robotics
16. Electrical Harmonies estimation in power systems using bat algorithm
17. CSBIIST: Cuckoo Search based intelligent Image segmentation technique
18. Improving Genetic Algorithm Solution’s Performance for Optimal Order Allocation in an E-Market with the Pareto Optimal Set
19. Multi-Robot Coordination Through Bio-Inspired Strategies
20. Optimization in Probabilistic Domains: An Engineering Approach
Product details
- No. of pages: 442
- Language: English
- Copyright: © Academic Press 2020
- Published: April 9, 2020
- Imprint: Academic Press
- eBook ISBN: 9780128226094
- Paperback ISBN: 9780128197141
About the Editor
Xin-She Yang

Affiliations and Expertise
Ratings and Reviews
There are currently no reviews for "Nature-Inspired Computation and Swarm Intelligence"