A Hybrid Optimization Algorithm and Its Application for Conformal Array Pattern Synthesis
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Bibliographic record
Abstract
Investigations on conformal phased array pattern synthesis using a novel hybrid evolutionary algorithm are presented. First, in order to overcome the drawbacks of the standard genetic algorithm (GA) and the particle swarm optimization (PSO), an improved genetic algorithm (IGA) and an improved particle swarm optimization (IPSO) algorithm are proposed by introducing novel mechanisms. Then, inspired by the idea of grafting in botany, a hybrid algorithm called HIGAPSO is proposed, which combines IGA and IPSO to take advantages of both methods. After that, a spherical array antenna using wide-band stacked patch antenna elements is selected as a synthesis example to illustrate the power of HIGAPSO in solving realistic optimization problems. Finally, HIGAPSO is used to optimize the amplitude of the element current excitation of the spherical conformal array. Experimental results show that the hybrid algorithm is superior to GAs and PSOs when applied to both the classical test function and the practical problem of conformal antenna array synthesis.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it