You are previewing Swarm Intelligence for Electric and Electronic Engineering.
O'Reilly logo
Swarm Intelligence for Electric and Electronic Engineering

Book Description

With growing developments in artificial intelligence and focus on swarm behaviors; algorithms have been utilized in solving a variety of problems in the field of engineering. This approach has been specifically suited to face the challenges in electric and electronic engineering. Swarm Intelligence for Electric and Electronic Engineering provides an exchange of knowledge on the advances, discoveries, and improvements of swarm intelligence in electric and electronic engineering. This comprehensive collection aims to bring together new swarm-based algorithms as well as approaches to complex problems and various real-world applications. 

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Editorial Advisory Board and List of Reviewers
    1. Editorial Advisory Board
    2. List of Reviewers
  5. Dedication
  6. Foreword
  7. Preface
  8. Section 1: Circuit Design
    1. Chapter 1: Design and Optimization of Microwave Circuits and Devices with the Particle Swarm Optimizer
      1. ABSTRACT
      2. INTRODUCTION
      3. 2 APPLICATION OF THE PSO TO THE DESIGN OF MICROWAVE CIRCUITS AND DEVICES
      4. 3 NUMERICAL RESULTS: SYNTHESIS OF MICROWAVE CIRCUITS AND DEVICES
      5. 4 COMPUTATIONAL ISSUES OF THE CIRCUITAL DESIGN METHODOLOGY
      6. CONCLUSION
    2. Chapter 2: Microwave Circuit Design
      1. ABSTRACT
      2. INTRODUCTION
      3. CONCLUSION
    3. Chapter 3: MO-TRIBES for the Optimal Design of Analog Filters
      1. ABSTRACT
      2. THE PROBLEM STATEMENT
      3. THE MULTIOBJECTIVE PARTICLE SWARM OPTIMIZATION TECHNIQUE: CONCEPTS AND FORMULATION
      4. TRIBES AND MO-TRIBES
      5. APPLICATION OF MO-TRIBES TO THE OPTIMAL DESIGN OF ANALOG FILTERS
      6. SUMMARY AND CONCLUSION
    4. Chapter 4: Design Automation, Modeling, Optimization, and Testing of Analog/RF Circuits and Systems by Particle Swarm Optimization
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. RF/ANALOG CIRCUIT DESIGN AND AUTOMATION: VARIOUS APPLICATIONS OF PSO
      4. 3. MODELING OF CIRCUITS
      5. 4. HIGH SPEED SYSTEM DESIGN PROBLEM: POWER INTEGRITY ISSUES
      6. 5. TESTING OF ANALOG CIRCUITS
      7. 6. DESIGNING PASSIVE CIRCUITS
      8. 7. MODIFIED PSO ALGORITHMS
      9. 8. CONCLUSION
  9. Section 2: Antenna and Optical Devices
    1. Chapter 5: Particle Swarm Optimization Algorithm in Electromagnetics- Case Studies
      1. ABSTRACT
      2. INTRODUCTION
      3. PARTICLE SWARM OPTIMIZATION: DEVELOPMENT, MODIFICATIONS
      4. PARTICLE SWARM OPTIMIZATION-RECONFIGURABLE RADIATORS
      5. PARTICLE SWARM OPTIMIZATION-CANCER DETECTION TECHNIQUES
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
    2. Chapter 6: Particle Swarm Optimization Algorithms Applied to Antenna and Microwave Design Problems
      1. ABSTRACT
      2. INTRODUCTION
      3. PARTICLE SWARM OPTIMIZATION: CLASSICAL ALGORITHMS AND VARIANTS
      4. APPLICATIONS, RESULTS, AND DISCUSSION
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
    3. Chapter 7: Optimum Design and Characterization of Rare Earth-Doped Fibre Amplifiers by Means of Particle Swarm Optimization Approach
      1. ABSTRACT
      2. BACKGROUND
      3. MAIN FOCUS OF THE CHAPTER
      4. THEORETICAL ANALYSIS
      5. NUMERICAL RESULTS
      6. CONCLUSION
    4. Chapter 8: Optimum Design of Hybrid EDFA/FRA by Particle Swarm Optimization
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. IMPLEMENTATION OF PSO ON OPTICAL AMPLIFIERS
      4. 3. HYBRID EDFA/FRA MODELING
      5. 4. RESULTS OF HYBRID EDFA/FRA OPTIMIZATION
      6. 5. CONCLUSION
  10. Section 3: Control Optimization
    1. Chapter 9: Distributed Task Allocation in Swarms of Robots
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. DISTRIBUTED TASK ALLOCATION
      5. EXPERIMENTAL EVALUATION
      6. TUNING OF CONTROL PARAMETERS
      7. CONCLUSION AND FUTURE RESEARCH
    2. Chapter 10: Using Swarm Intelligence for Optimization of Parameters in Approximations of Fractional-Order Operators1
      1. ABSTRACT
      2. INTRODUCTION: MATHEMATICAL BACKGROUND AND LITERATURE REVIEW
      3. APPROXIMATION OF FRACTIONAL ORDER OPERATORS
      4. PARTICLE SWARM OPTIMIZATION OF FRACTIONAL ORDER OPERATORS
      5. SIMULATION RESULTS
      6. CONCLUSION
    3. Chapter 11: Optimal Location of the Workpiece in a PKM-based Machining Robotic Cell
      1. ABSTRACT
      2. INTRODUCTION
      3. PKM CONFIGURATION AND MODELLING
      4. STRUCTURAL OPTIMIZATION
      5. PARTICLE SWARM OPTIMIZATION
      6. STRUCTURAL OPTIMIZATION RESULTS
      7. WORKPIECE OPTIMAL LOCATION
      8. CONCLUSION
    4. Chapter 12: The Generalized Particle Swarm Optimization Algorithm
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. GENERALIZED PARTICLE SWARM OPTIMIZATION
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
  11. Section 4: Scheduling and Diagnosis
    1. Chapter 13: Transmission Expansion Planning by using DC and AC Models and Particle Swarm Optimization
      1. ABSTRACT
      2. INTRODUCTION
      3. THE TRANSMISSION EXPANSION PLANNING PROBLEM USING DC AND AC MODELS
      4. PARTICLE SWARM OPTIMIZATION VARIANTS
      5. IMPLEMENTATION ISSUES
      6. TEST RESULTS
      7. FUTURE RESEARCH DIRECTIONS
      8. CONCLUSION
    2. Chapter 14: Short-Term Generation Scheduling Solved with a Particle Swarm Optimizer
      1. ABSTRACT
      2. INTRODUCTION
      3. GENERATION PLANNING MODELS USED IN POWER SYSTEMS
      4. SIMULATIONS AND RESULTS
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
      7. APPENDIX: NOMENCLATURE
    3. Chapter 15: Nondestructive Analysis of Dielectric Bodies by Means of an Ant Colony Optimization Method
      1. ABSTRACT
      2. INTRODUCTION
      3. 2. MATHEMATICAL FORMULATION
      4. 3. ANT COLONY OPTIMIZATION
      5. 5. CONCLUSION
    4. Chapter 16: The Use of Evolutionary Algorithm-Based Methods in EEG Based BCI Systems
      1. ABSTRACT
      2. INTRODUCTION
      3. A BRIEF INTRODUCTION TO SOME EVOLUTIONARY METHODS
      4. CONCLUSION
  12. Compilation of References
  13. About the Contributors