Book description
Swarm intelligence is one of the fastest growing subfields of artificial intelligence and soft computing. This field includes multiple optimization algorithms to solve NP-hard problems for which conventional methods are not effective. It inspires researchers in engineering sciences to learn theories from nature and incorporate them.
Swarm Intelligence: Foundation, Principles, and Engineering Applications provides a comprehensive review of new swarm intelligence techniques and offers practical implementation of Particle Swarm Optimization (PSO) with MATLAB code. The book discusses the statistical analysis of swarm optimization techniques so that researchers can analyse their experiment design. It also includes algorithms in social sectors, oil and gas industries, and recent research findings of new optimization algorithms in the field of engineering describing the implementation in machine learning.
This book is written for students of engineering, research scientists, and academicians involved in the engineering sciences.
Table of contents
- Cover
- Half Title
- Series Page
- Title Page
- Copyright Page
- Table of Contents
- Preface
- Acknowledgements
- Authors
- Chapter 1 Swarm Intelligence: Review, Perspective, and Challenges
-
Chapter 2 Theory to Practice in PSO
- 2.1 Introduction
- 2.2 Mathematical Modeling
-
2.3 Advances in PSO
- 2.3.1 Comprehensive Learning Particle Swarm Optimization (CLPSO)
- 2.3.2 Heterogeneous Comprehensive Learning Particle Swarm Optimization
- 2.3.3 Extraordinary Particle Swarm Optimization
- 2.3.4 Improved Random Drift PSO (IRDPSO)
- 2.3.5 Autonomous Particle Groups for Particle Swarm Optimization (AGPSO)
- 2.3.6 Improved Particle Swarm Optimization Using Dynamic Parameter Configuration
- 2.3.7 Fractional-Order Darwinian PSO
- 2.3.8 Guaranteed Convergence PSO (GCPSO)
- 2.3.9 Vector-Evaluated PSO (VEPSO)
- 2.4 Hybrid PSO
- 2.5 Conclusion
- References
- Chapter 3 Survey on New Swarm Intelligence Algorithms
-
Chapter 4 Engineering Applications of Swarm Intelligence
- 4.1 Application in Electrical Engineering
- 4.2 Application in Robotics Engineering
- 4.3 Application in Electronics Engineering
- 4.4 Conclusion
- References
-
Chapter 5 Swarm Intelligence Applications in Artificial Neural Networks
- 5.1 Introduction
- 5.2 Artificial Neural Networks Architecture
- 5.3 Conventional Learning Algorithm
- 5.4 Swarm Intelligence-Based Artificial Neural Network
- 5.5 Conclusion
- References
- Index
Product information
- Title: Swarm Intelligence
- Author(s):
- Release date: February 2022
- Publisher(s): CRC Press
- ISBN: 9781000529753
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