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1st Edition - April 9, 2020
Editor: Xin-She Yang
Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization, computational intelligence, soft computing and… Read more
Immediately download your ebook while waiting for your print delivery. No promo code is needed.
Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization, computational intelligence, soft computing and data science. Recently, the literature in the field has expanded rapidly, with new algorithms and applications emerging.
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.
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
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