Numerical and experimental generated data during project https://doi.org/10.1038/s41598-023-44023-8

Description

The dataset was generated using a procedure for global optimization of antenna structures. Our methodology involves a simplex-based automated search performed at the level of approximated operating and performance figures of the structure at hand. The approach capitalizes on weakly-nonlinear dependence between the operating figures and antenna geometry parameters, as well as computationally cheap design updates, only requiring a single EM analysis per iteration. Formal convergence of the algorithm is guaranteed by implementing the automated decision-making procedure for reducing the simplex size upon detecting the lack of objective function improvement. The global optimization stage is succeeded by gradient-based parameter refinement.

Dataset file

metadata_p23_complete.pdf

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Attribution

Details

Year of publication:

2025

Verification date:

2025-03-17

Dataset language:

English

DOI:

10.34808/bqg6-p634

Funding:

Unsupervised specification-driven design of antenna structures using artificial intelligence and machine learning

Verified by:

Gdańsk University of Technology

Keywords

References

publication High-Efficacy Global Optimization of Antenna Structures by Means of Simplex-Based Predictors

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Authors

Sławomir Kozieł prof. dr inż.
Politechnika Gdańska - Katedra Systemów Mikroelektronicznych
orcid number 0000-0002-9063-2647open in new tab
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