Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications
Editat de Xin She Yangen Limba Engleză Paperback – 10 apr 2020
Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is a timely reference giving a comprehensive review of relevant state-of-the-art developments in algorithms, theory and applications of nature-inspired algorithms and swarm intelligence. It reviews and documents the new developments, focusing on nature-inspired algorithms and their theoretical analysis, as well as providing a guide to their implementation. The book includes case studies of diverse real-world applications, balancing explanation of the theory with practical implementation.
Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is suitable for researchers and graduate students in computer science, engineering, data science, and management science, who want a comprehensive review of algorithms, theory and implementation within the fields of nature inspired computation and swarm intelligence.
- 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
Preț: 652.20 lei
Preț vechi: 967.73 lei
-33% Nou
Puncte Express: 978
Preț estimativ în valută:
124.82€ • 129.32$ • 104.17£
124.82€ • 129.32$ • 104.17£
Carte tipărită la comandă
Livrare economică 14-28 martie
Preluare comenzi: 021 569.72.76
Specificații
ISBN-13: 9780128197141
ISBN-10: 0128197145
Pagini: 442
Ilustrații: Approx. 150 illustrations
Dimensiuni: 191 x 235 mm
Greutate: 0.75 kg
Editura: ELSEVIER SCIENCE
ISBN-10: 0128197145
Pagini: 442
Ilustrații: Approx. 150 illustrations
Dimensiuni: 191 x 235 mm
Greutate: 0.75 kg
Editura: ELSEVIER SCIENCE
Public țintă
Researchers, advanced undergraduate and graduate students in computer science, engineering, optimization, data science, and management scienceCuprins
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 communicatinon
Part II: Theory and Analysis
5. Mathematical Foundations for Algorithm Analysis
6. Probability Theory for Analysing Nature-Inspired Algorithms
7. Theoretical Framework for Algorithm Analysis
Part 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
2. Bat Algorithm and Cuckoo Search Algorithms
3. Firefly Algorithm and Flower Pollination Algorithm
4. Bio-inspired Algorithms: Principles, Implementation and Applications to wireless communicatinon
Part II: Theory and Analysis
5. Mathematical Foundations for Algorithm Analysis
6. Probability Theory for Analysing Nature-Inspired Algorithms
7. Theoretical Framework for Algorithm Analysis
Part 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