Research on the Optimization of Boiler Efficiency based on Artificial Bee Colony Algorithm
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 paper is to seek effective scheme of boiler efficiency optimization, it uses Artificial Bee Colony (ABC) algorithm to optimize boiler efficiency based on the model of boiler combustion efficiency. First, an optimization model of boiler efficiency, which takes boiler efficiency function as optimization objective, is set up according to the heat loss of boiler combustion. Moreover, the operating parameters affecting boiler efficiency is determined. Then ABC algorithm is used to solve the optimal value of boiler efficiency. The result of the research shows that the optimization of boiler efficiency based on ABC algorithm can quickly obtain optimal parameters for running boiler, so that the optimal boiler efficiency can be got.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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