Self‐optimization for smelting process of fused magnesium furnace based on operation status assessment
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
Abstract Based on operation status assessment and self‐optimizing regulation, an optimization strategy for the smelting process of a fused magnesium furnace is proposed to improve the benefits of smelting magnesia. In the online evaluation stage, according to the qualitative information, the data is divided by the fuzzy model recognition method, and then the posterior probability of online data in different Gaussian mixture models is calculated to obtain the evaluation results. When the evaluation results are not optimal, the non‐optimal variables are obtained by calculating the contribution rate, and then the self‐optimizing adjustment is carried out by case search. In order to improve the recovery rate of self‐optimizing regulation, a time series prediction method is used to predict the operation status, and the corresponding operation schemes for different prediction results are proposed. Experimental results show that the proposed method is accurate and effective.
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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