Development of an inexact fuzzy flexible programming approach for environmental pollution control
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
Abstract Optimization techniques have been widely applied to solving environmental management problems, particularly for regional air quality management systems where potential air pollutions arising from improper management would seriously threaten human health. An inexact fuzzy flexible programming approach is developed to facilitate decision support for air quality management. It can tackle both stipulation uncertainty and parameter uncertainty in the objective function and constraints. Upon the previous research efforts, the most significant improvement of this approach is the introduction of multiple control variables corresponding to the objective function and all constraints. This attempt makes it possible for the constraints to be relaxed under respective levels, such that a more satisfactory objective value may be obtained. The impact of each constraint on the system outputs can also be further interpreted. The proposed approach would be helpful for such systems where the decision makers prefer to not only find out an air pollution control scheme with a satisfaction level as high as possible, but also mitigate the uncertainty in decision making. A regional air pollution control problem is then studied to demonstrate the applicability of the developed approach. A variety of management strategies for air pollutants allocation and treatment are suggested in terms of the optimal solutions to decision variables. Comparison between the optimal solutions from the proposed approach and those from a conventional fuzzy flexible programming model is undertaken. It can be found that neither the management strategies nor the priorities of pollutants allocation obtained from the two models are the same. The satisfaction level of the proposed approach (taking the average value of optimized solutions of control variables for comparison) is always higher than that of the existing approach, indicating the superiority of the proposed approach in handling many air pollution control problems. Keywords: air pollutioninexactuncertaintyfuzzy flexible programmingoptimization Acknowledgements This research was supported by the Major State Basic Research Development Program (2005CB724200 and 2006CB403307), and the Natural Science and Engineering Research Council of Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| 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