Developing a water quality model using fuzzy approach for the Al-Gharraf River in Southern Iraq
Bibliographic record
Abstract
The present study develops a water quality model based on fuzzy approach to assessment of the surface water quality in Al-Gharraf River located in the South of Iraq. The water quality parameters, including Total Dissolved Solids (TDS), Biological Oxygen Demand (BOD), Chloride (CL), Sulphate (SO4), Nitrate (NO3), and Phosphate (PO4), were selected as input parameters to fuzzy water quality model (FWQ). To evaluate the performance of the proposed model (FWQ) of Al-Gharraf River in the period of the study, the produces of our model were compared with those of the water quality index (WQI) and Canadian Water Quality Index (CWQI). They showed similar results and were sensitive to changes in the level of water quality parameters. However, the model proposed in the present study produced a more stringent produces compared to the WQI and CWQI. Results from the simulation indicate that the sensitivity analysis of the suggested approach will be improved by almost (17%, and 24%) more than that achieved by the processes WQI and CWQI, respectively. In conclusion, the proposed index seems to produce accurate and reliable results and can be used as a comprehensive tool for water quality assessment.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".