Description
The dataset was generated using a procedure for efficient global optimization (EGO) of multiband antennas, where the surrogate is repeatedly built and refined using custom-defined response features. The infill criteria are based on minimizing a surrogate-evaluated objective function, whereas the underlying optimization engine is the particle swarm optimization algorithm (PSO). Comprehensive benchmarking demonstrates the superiority of the presented approach over surrogate-assisted methods handling antenna frequency responses, as well as direct nature-inspired optimization.
Dataset file
metadata_p19_complete.pdf
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File details
- License:
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CC BYAttribution
Details
- Year of publication:
- 2025
- Verification date:
- 2025-03-17
- Dataset language:
- English
- DOI:
- DOI ID 10.34808/jkz5-v852 open in new tab
- Funding:
- Verified by:
- Gdańsk University of Technology
Keywords
- Antennas
- global parameter tuning
- kriging interpolation
- nature-inspired optimization
- response features
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