Multifidelity Surrogate Modeling Based on Analytical Eigenfunction Expansions
Author:
Affiliation:
1. Department of Electrical and Computer Engineering, Florida International University College of Engineering and Computing, Miami, FL, USA
Funder
Air Force Office of Scientific Research
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/8/10035677/09992009.pdf?arnumber=9992009
Reference30 articles.
1. Constrained multi-objective antenna design optimization using surrogates
2. Low-Cost Data-Driven Surrogate Modeling of Antenna Structures by Constrained Sampling
3. Predicting the output from a complex computer code when fast approximations are available
4. A Multi-Fidelity Surrogate Optimization Method Based on Analytical Models
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1. A Deep Learning Convolutional Neural Network for Antenna Near-Field Prediction and Surrogate Modeling;IEEE Access;2024
2. Numerical Eigenfunction Expansions for Optimizing Arbitrarily-Shaped Patch Antennas;2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (USNC-URSI);2023-07-23
3. Prospect of Dynamic Metasurface Array Antenna System With Machine Learning;Advances in Wireless Technologies and Telecommunication;2023-06-30
4. Multi-Fidelity Surrogate Modeling based on Numerical Eigenfunction Expansions;2023 International Applied Computational Electromagnetics Society Symposium (ACES);2023-03-26
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