A Hybrid Algorithm for Electromagnetic Optimization Utilizing Neural Networks

Yanan Liu, Tianjian Lu, Ken Wu, Jian Ming Jin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose a hybrid algorithm for electromagnetic optimization. The algorithm combines the genetic algorithm and gradient based optimization, leveraging the power of neural networks in both. The effectiveness and efficiency of the proposed algorithm are demonstrated using antenna and microwave filter design examples.

Original languageEnglish (US)
Title of host publicationEPEPS 2018 - IEEE 27th Conference on Electrical Performance of Electronic Packaging and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages261-263
Number of pages3
ISBN (Electronic)9781538693032
DOIs
StatePublished - Nov 13 2018
Event27th IEEE Conference on Electrical Performance of Electronic Packaging and Systems, EPEPS 2018 - San Jose, United States
Duration: Oct 14 2018Oct 17 2018

Publication series

NameEPEPS 2018 - IEEE 27th Conference on Electrical Performance of Electronic Packaging and Systems

Other

Other27th IEEE Conference on Electrical Performance of Electronic Packaging and Systems, EPEPS 2018
CountryUnited States
CitySan Jose
Period10/14/1810/17/18

Keywords

  • Genetic algorithms
  • Neural networks
  • Optimization

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality
  • Electronic, Optical and Magnetic Materials

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  • Cite this

    Liu, Y., Lu, T., Wu, K., & Jin, J. M. (2018). A Hybrid Algorithm for Electromagnetic Optimization Utilizing Neural Networks. In EPEPS 2018 - IEEE 27th Conference on Electrical Performance of Electronic Packaging and Systems (pp. 261-263). [8534264] (EPEPS 2018 - IEEE 27th Conference on Electrical Performance of Electronic Packaging and Systems). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EPEPS.2018.8534264