Optimum design of steel telecommunication poles using genetic algorithms
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
This study implements the genetic algorithm (GA) method in the optimization of steel telecommunication poles subjected to normal operating loads. In formulating the optimization problem, the objective function is defined as the pole weight. The imposed constraints on the design are: interaction ratios, sway angle limitations, minimum and maximum pole bottom diameters, and segment heights. The formulated problem is a mixed continuous–discrete problem where the main dimensions of the pole, top and bottom diameters, and segment heights are continuous variables whereas other variables are discrete. A Microsoft ® Visual Basic ® computer program is written implementing the requirements of TIA/EIA-222-G standards and using genetic algorithms (GAs). A verification problem and a generic telecommunication pole example are presented that show the effectiveness of the proposed approach. This program can be extended to cover other design standards of telecommunication poles as well as different types of poles, such as lighting and transmission poles.
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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