Enhanced Artificial Immune System Algorithm and Its Comparison to Bio-Inspired Optimization Techniques for Electromagnetics Applications

Authors

  • Ozlem Kilic Department of Electrical Engineering and Computer Science The Catholic University of America, Washington, DC, 20064, USA
  • Quang M. Nguyen Department of Electrical Engineering and Computer Science The Catholic University of America, Washington, DC, 20064, USA

Keywords:

Antireflective surface, artificial immune system (AIS), bio-inspired optimization, enhanced artificial immune system (EAIS), microstrip (EBG), particle swarm optimization (PSO)

Abstract

This paper introduces an enhanced artificial immune system algorithm (EAIS) that benefits from a hybrid approach by integrating concepts from the genetic algorithm (GA) and particle swarm optimization (PSO). The potential of the EAIS algorithm is demonstrated by comparing its performance with other bio-inspired optimization algorithms; namely the particle swarm optimization (PSO) and the conventional artificial immune system (AIS) when applied to two electromagnetics applications, such as the design of antireflective surfaces, and microstrip electromagnetic band gap (EBG) structures.

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References

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Published

2021-07-25

How to Cite

[1]
Ozlem Kilic and Quang M. Nguyen, “Enhanced Artificial Immune System Algorithm and Its Comparison to Bio-Inspired Optimization Techniques for Electromagnetics Applications”, ACES Journal, vol. 33, no. 02, pp. 132–135, Jul. 2021.

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General Submission