Modeling of a drying process using subtractive clustering based system identification
Why this work is in the frame
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Bibliographic record
Abstract
This paper describes the modeling of an industrial drying process into a three-input one-output first order Sugeno system. An objective system model is identified from input-output data of the system by applying the subtractive clustering algorithm. The input-output data represents process parameters measured during the drying of starch in a jet spouted dryer. Minimum error models are obtained through enumerative search of clustering parameters. A set of checking data is used to verify the model output. The optimal model, as well as its output, is presented. The step size used in the clustering parameter search is varied and its influence on the modeling performance is presented. Models obtained by setting the same cluster radius for all data dimensions and models obtained by setting a cluster radius for each data dimension are computed and their performance is compared.
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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