A Dual Kriging Approach With Improved Points Selection Algorithm for Memory Efficient Surrogate Optimization in Electromagnetics-Reference-Cited by-同舟云学术

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A Dual Kriging Approach With Improved Points Selection Algorithm for Memory Efficient Surrogate Optimization in Electromagnetics

Published:2016-03 Issue:3 Volume:52 Page:1-4
ISSN:0018-9464
Container-title:IEEE Transactions on Magnetics
language:
Short-container-title:IEEE Trans. Magn.

Author:

Li Yinjiang,Xiao Song,Rotaru Mihai,Sykulski Jan K.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Electronic, Optical and Magnetic Materials

Link

http://xplorestaging.ieee.org/ielx7/20/7410156/7289433.pdf?arnumber=7289433

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Knowledge‐Based Globalized Optimization of High‐Frequency Structures Using Inverse Surrogates;Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning;2023-08-30

2. Kriging Methodology for Predicting Material Uncertainty Impact on FEM Scattering Computations;2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (USNC-URSI);2023-07-23

3. Globalized Parametric Optimization of Microwave Passive Components Using Simplex-Based Surrogates;IEEE Transactions on Microwave Theory and Techniques;2023

4. Machine Learning Application for Modeling and Design Optimization of High Frequency Structures;Advances in Time‐Domain Computational Electromagnetic Methods;2022-11

5. Direct constraint control for EM-based miniaturization of microwave passives;Scientific Reports;2022-08-03

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