Numerical and experimental generated data during project https://doi.org/10.1038/s41598-024-80182-y - Open Research Data - Bridge of Knowledge

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Numerical and experimental generated data during project https://doi.org/10.1038/s41598-024-80182-y

Description

The dataset was generated using a machine learning procedure for cost-effective global optimization-based miniaturization of antennas. The technique included parameter space pre-screening and the iterative refinement of kriging surrogate models using the predicted merit function minimization as an infill criterion.

Numerical experiments conducted on four broadband antennas indicated that the proposed framework consistently yielded competitive miniaturization rates across multiple algorithm runs at low costs, compared to the benchmark.

Dataset file

metadata_p2_complete.pdf
1.4 MB, S3 ETag f7004e55312ffa8f4490377ed2d28ee0-1, downloads: 0
The file hash is calculated from the formula
hexmd5(md5(part1)+md5(part2)+...)-{parts_count} where a single part of the file is 512 MB in size.

Example script for calculation:
https://github.com/antespi/s3md5

File details

License:
Creative Commons: by 4.0 open in new tab
CC BY
Attribution

Details

Year of publication:
2025
Verification date:
2025-03-17
Dataset language:
English
Fields of science:
  • automation, electronics, electrical engineering and space technologies (Engineering and Technology)
DOI:
DOI ID 10.34808/spvb-fq56 open in new tab
Funding:
Verified by:
Gdańsk University of Technology

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