Bio-Inspired Computational Algorithms and Their Applications
eBook - PDF

Bio-Inspired Computational Algorithms and Their Applications

  1. 434 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Bio-Inspired Computational Algorithms and Their Applications

About this book

Bio-inspired computational algorithms are always hot research topics in artificial intelligence communities. Biology is a bewildering source of inspiration for the design of intelligent artifacts that are capable of efficient and autonomous operation in unknown and changing environments. It is difficult to resist the fascination of creating artifacts that display elements of lifelike intelligence, thus needing techniques for control, optimization, prediction, security, design, and so on. Bio-Inspired Computational Algorithms and Their Applications is a compendium that addresses this need. It integrates contrasting techniques of genetic algorithms, artificial immune systems, particle swarm optimization, and hybrid models to solve many real-world problems. The works presented in this book give insights into the creation of innovative improvements over algorithm performance, potential applications on various practical tasks, and combination of different techniques. The book provides a reference to researchers, practitioners, and students in both artificial intelligence and engineering communities, forming a foundation for the development of the field.

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Yes, you can access Bio-Inspired Computational Algorithms and Their Applications by Shangce Gao 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. Bio-Inspired Computational Algorithms and Their Applications
  2. Contents
  3. Preface
  4. Part 1 Recent Development of Genetic Algorithm
  5. Part 2 New Applications of Genetic Algorithm
  6. Part 3 Artificial Immune Systems and Swarm Intelligence
  7. Part 4 Hybrid Bio-Inspired Computational Algorithms