An optimization technique for cropping patterns and land consolidation: A case study for irrigation network
Bibliographic record
Abstract
During the past few decades, there has been growing interest in water resources management. Presently, there are many areas in middle east facing with shortage of water for agricultural activities. Therefore, there is a growing concern to have efficient usage of water through optimization techniques. This paper presents a study to maximize famers' revenue by developing a mathematical model subject to some land and water constraints. The proposed study has been applied for a case study of agricultural program in city of Abhar, Iran and the preliminary results indicate that it could increase the efficiency of agricultural program, significantly. In our survey, the optimal cultivation yields for four five-year programs have increased the income by 20.81, 44.698, 87.18 and 250.34 percent, respectively. In addition, 7.27% development land is added to agricultural lands, there is a 17% increase in water utilization and the productivity is increased from 50% to well above 77% after four 5-year programs have been implemented.
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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 | 0.001 | 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".