An optimisation-based environmental decision support system for sustainable development in a rural area in China
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
Sustainable development has been widely recognised as an effective means for harmonising human society and natural systems. However, achieving the goal of sustainability is difficult since many conflicting factors have to be balanced due to the complexities of real-world problems. Previously, many efforts have been made to clarify the concept of sustainable development and to develop related theoretical and practical tools. Nevertheless, there is still a lack of effective methods that can integrate optimisation of resources allocation and visualisation of spatial and temporal dimensions of socio-economic and environmental interactions within a general framework. In this study, an optimisation-based environmental decision support system (EDSS) was developed for supporting sustainable rural development. The system included a dynamic database system, a graphical user interface, and a mixed integer linear programming (MILP) model. Yongxin County, located in Jiangxi Province, China, was chosen as the study case for applying the proposed EDSS. The county has encountered problems of serious conflicts among rapid economic development, ecological destruction and environmental deterioration. The study results demonstrated that EDSS could help analyse the complex relationships among multiple socio-economic and environmental factors, and provide recommendations of scientific management strategies for achieving local sustainability.
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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 | 0.000 | 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 it