Research on load identification of mine hoist based on improved support vector machine
Why this work is in the frame
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Bibliographic record
Abstract
To solve the problem of indirect identification of dynamic load of a mine hoist, a novel identification method based on running speed is proposed. In this paper, the simulation model with variable frequency speed regulation by vector control was established in Matlab/Simulink. By setting the acceleration of different time periods, the mine hoist running characteristics under different loads can be accurately simulated, and the coupling relationship between the running speed characteristic and the system load characteristic can be obtained. The support vector machine (SVM) with grid search(GS)/genetic algorithms (GA)/ particle swarm optimization (PSO) is used to estimate the mine hoist load. Grid search turns out to be a better optimizing method than either GA or PSO. It is found that by adjusting the proportional relationship of the dependent variable and then doing the load identification by SVM of GS, the load identification effect can be greatly improved. The method is also applicable when dealing with similar data distributions.
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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 | 0.001 | 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