Analyzing of Reduction Process of Urban Open Spaces in Process of Cities Development with Emphasis on Crisis Management in Tehran Metropolis
Bibliographic record
Abstract
Urbanism is effective science in order to reduction damages while accruing disaster. Indeed, urbanism is important in term of natural crisis due to have key role in physical development process. Today one of the most important issues in Tehran metropolis is shortage of usable open spaces in crisis conditions because there is proportion between built spaces, building density and usable open spaces in crisis conditions. It is clearly that could be used from open spaces in crisis conditions as relief base and temporary accommodation. The main issue in order to studying in dynamic systems is reduction process of urban open spaces with usable in crisis conditions. So in this research have been defined new mechanisms and policies in order to modification of destructive mechanism by studying of effective mechanisms and identifying cause-effect structure. In this study, at first was determined system boundary and effective endogenous and exogenous variables. Then, was studied reference variable behavior. After that were determined dynamic assumptions and was prepared conceptual model and cause-effect diagrams. At finally, modeling was performed by definition of parameters and structuring of dynamic theories in “Vensim PLE” Software for 20 years periods. The obtained model was tested in extreme conditions.Analyzing of reduction process of urban open spaces in process of cities development in Tehran metropolis is the purpose of this research. The research method is analysis – descriptive. Also data collected is documents – field. The results show that will be controlled reduction process of urban open spaces with usable in crisis conditions in Tehran metropolis by modification of destructive mechanisms also using policies that associated with key variables.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".