A Novel Genetic Programming Approach for Frequency-Dependent Modeling
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Frequency-dependent modeling of devices and systems is a common practice in several fields, such as power systems, microwave systems, and electronics systems. The modeling process usually involves converting the tabulated frequency-response data into a compact equivalent circuit model. The main drawback of the currently existing methods such as vector fitting is that the obtained model is often nonpassive, leading to unstable simulations. In order to overcome this problem, this paper proposes a genetic programming (GP) approach to generate equivalent circuits with guaranteed passivity. The proposed method starts with a nonoptimal initial equivalent circuit. Both the elements and the topology of this circuit are then evolved by the proposed GP-based method, and an accurate equivalent circuit is obtained. Key ideas and detailed algorithms are presented in this paper. Finally, the performance of the proposed method is verified by using different case studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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