Advances in Evolutionary Algorithms
eBook - PDF

Advances in Evolutionary Algorithms

  1. 480 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Advances in Evolutionary Algorithms

About this book

With the recent trends towards massive data sets and significant computational power, combined with evolutionary algorithmic advances evolutionary computation is becoming much more relevant to practice. Aim of the book is to present recent improvements, innovative ideas and concepts in a part of a huge EA field.

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Yes, you can access Advances in Evolutionary Algorithms by Witold Kosinski in PDF and/or ePUB format, as well as other popular books in Computer Science & Programming Algorithms. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Advances in Evolutionary Algorithms
  2. 1. Limit Properties of Evolutionary Algorithms
  3. 2. Evolutionary Systems Identification:New Algorithmic Concepts and Applications
  4. 3. FPBIL: A Parameter-free Evolutionary Algorithm
  5. 4. A Memetic Algorithm Assisted by an AdaptiveTopology RBF Network and Variable LocalModels for Expensive Optimization Problems
  6. 5. An Adaptive Evolutionary Algorithm Combining Evolution Strategy and Genetic Algorithm (Application of Fuzzy Power System Stabilizer)
  7. 6. A Simple Hybrid Particle Swarm Optimization
  8. 7. Recent Advances in Harmony Search
  9. 8. A Hybrid Evolutionary Algorithm and itsApplication to Parameter Identification ofRolling Elements Bearings
  10. 9. Domain Decomposition Evolutionary Algorithmfor Multi-Modal Function Optimization
  11. 10. Evolutionary Algorithms with DissortativeMating on Static and Dynamic Environments
  12. 11. Adapting Genetic Algorithms for Combinatorial Optimization Problems inDynamic Environments
  13. 12. Agent-Based Co-Evolutionary Techniques forSolving Multi-Objective Optimization Problems
  14. 13. Evolutionary Multi-Objective Robust Optimization
  15. 14. Improving Interpretability of Fuzzy ModelsUsing Multi-ObjectiveNeuro-Evolutionary Algorithms
  16. 15. Multi-objective Uniform-diversityGenetic Algorithm (MUGA)
  17. 16. EA-based Problem Solving Environment over the GRID
  18. 17. Evolutionary Methods for Learning BayesianNetwork Structures
  19. 18. Design of Phased Antenna Arrays using Evolutionary Optimization Techniques
  20. 19. Design of an Efficient Genetic Algorithm toSolve the Industrial Car Sequencing Problem
  21. 20. Symbiotic Evolution Genetic Algorithms forReinforcement Fuzzy Systems Design
  22. 21. Evolutionary Computation Applied to Urban Traffic Optimization
  23. 22. Evolutionary Algorithms in Decision Tree Induction