Strategic Planning of the Environmental Sustainable Development: A Case of Imam Khomeini Port
Bibliographic record
Abstract
The purpose of the present study is to compile the strategic planning of environmental sustainable development of Imam Khomeini port. Today, urban regions are regarded as the most basic units of global economic space. The planning on such regions is of high importance because it influences various aspects of human life. Previously, it was supposed that urban issues could be recognized and managed by intellection and science. Nevertheless, in recent years the attitude of system planning and sustainable development perspective have been included in urban planning studies that made serious doubts on this attitude to urban planning. SWOT is one of the most significant models of strategic planning which is used for identification of the strengths and weaknesses of internal and external environment of Imam Khomaini port for sustainable development planning. To this end, natural environment, physical and human systems were investigated through GPS data, synoptic stations, geology data, census and urban comprehensive and developing plan. The results showed that positive and negative points of sub-systems i.e., weaknesses and threats were more than the opportunities and strong points of the system. Moreover, most of the internal negative points were related to the natural sub-system and most of the external threats were related to the physical aspects. According to the results, two main strategies including settling the buildings in the most appropriate direction towards climatic conditions and adapting the accessibility networks with principles of special climatic planning of passages are suggested.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".