Nature-Inspired Computation and Swarm Intelligence

Xin-She Yang obtained his DPhil in Applied Mathematics from the University of Oxford. He then worked at Cambridge University and National Physical Laboratory (UK) as a Senior Research Scientist. He is currently a Reader in Modelling and Simulation at Middlesex University London, Fellow of the Institute of Mathematics and its Application (IMA) and a Book Series Co-Editor of the Springer Tracts in Nature-Inspired Computing. He has published more than 25 books and more than 400 peer-reviewed research publications with over 82000 citations, and he has been on the prestigious list of highly cited researchers (Web of Sciences) for seven consecutive years (2016-2022).

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