A fuzzy logic model for biogas generation in bioreactor landfillsA paper submitted to the Journal of Environmental Engineering and Science.
Bibliographic record
Abstract
A fuzzy logic model was developed to simulate the effect of leachate recirculation and sludge addition on the biogas generation in anaerobic bioreactor landfills. The model was designed using a fuzzy logic system (FLS) which incorporated 3 input variables (time, leachate recirculation, and sludge addition) and a single manipulated output (biogas generation rate). The biogas production rate was measured during the experiment and was increasing proportionally with the rate of both leachate recirculation and sludge addition. The experimental work involved the operation of six simulated laboratory-scale bioreactors for over a year under different operating schemes. The experimental results were employed in formulating the fuzzy rule base, calibrating the model, and verifying its predictions. Then, the model was validated against other measured data that was compiled from published studies. The FLS model simulations demonstrated high correlation with the experimental observations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".