Optimization of Landscape Path and Facility Layout in Public Environment Design Based on Ant Colony Algorithm
Bibliographic record
Abstract
As a key component of urban environmental resources, the design of landscape paths and facility layouts of urban public environments is not only related to the overall aesthetics of the city, but also to the quality of life of urban residents.In this paper, from the perspective of landscape layout, the ecological landscape spatial network is constructed by calculating the ecological landscape environmental adaptation degree and the ecological landscape pattern index.On this basis, the traditional ant colony algorithm is introduced and its heuristic function and path selection are improved, and the adaptive adjustment factor and angle guiding factor are added to improve the diversity and efficiency of path searching, so that the landscape layout optimization model based on the ant colony algorithm is obtained.Using this model to design a landscape layout optimization scheme for a scenic spot, the average fulfillment time of the optimized landscape path is 20.73 minutes, which is 19.52 minutes shorter than the average fulfillment time of the original planning scheme, indicating that the model in this paper is able to carry out the landscape layout optimization design effectively.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".