Aircraft total turnaround time estimation using fuzzy critical path method
Bibliographic record
Abstract
Airport Collaborative Decision Making (ACDM) flight scheduling plans rely on accurate predictions of both optimal and reliable aircraft turnaround times, which is one of the most difficult things to complete. In order to account for the effects of randomness and fuzziness on the turnaround process duration, this paper deals with transforming the probability distribution of well-fitted sub-processes into a cumulative density function, which is equivalent to the fuzzy membership function (FMF), and then using goodness-of-fit to determine the fuzzy membership grade of each turnaround sub-process. The turnaround time is calculated using the fuzzy critical path method (FCPM), which is a combination of the Critical Path Method (CPM) and fuzzy set theory. In order to verify this estimate, we created the FMF using historical data and compared it to turnaround times based on FCPM. A linear regression model is used to examine the relationship between arrival delays and the FCPM-based turnaround process. We also use historical data to generate fuzzy sets of different arrival delays using Frankfurt airport data from the summer of 2017 and conclude that delays are positively correlated with the FCPM-based turnaround process.
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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 | 0.001 | 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 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".