A Hybrid Electromagnetic Optimization Method Based on Physics-Informed Machine Learning-Reference-Cited by-同舟云学术

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A Hybrid Electromagnetic Optimization Method Based on Physics-Informed Machine Learning

Published:2024 Issue: Volume:9 Page:157-165
ISSN:2379-8815
Container-title:IEEE Journal on Multiscale and Multiphysics Computational Techniques
language:
Short-container-title:IEEE J. Multiscale Multiphys. Comput. Tech.

Author:

Liu Yanan¹^ORCID,Li Hongliang²^ORCID,Jin Jian-Ming¹^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Champaign, IL, USA

2. Resonant, Inc., San Mateo, CA, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7274859/10296074/10493126.pdf?arnumber=10493126

Reference32 articles.

1. An Efficient Method for Antenna Design Optimization Based on Evolutionary Computation and Machine Learning Techniques

2. An Efficient Method for Complex Antenna Design Based on a Self Adaptive Surrogate Model-Assisted Optimization Technique

3. EM-Based Optimization of Microwave Circuits Using Artificial Neural Networks: The State-of-the-Art

4. EM-Based Monte Carlo Analysis and Yield Prediction of Microwave Circuits Using Linear-Input Neural-Output Space Mapping

5. Advanced RF and Microwave Design Optimization: A Journey and a Vision of Future Trends

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