Super-Resolution Method for Radio Wave Propagation in Tunnels: A Comparison of Data Processing Strategies in Modeling
Bibliographic record
Abstract
The vector parabolic equation (VPE) method is widely adopted for modeling radio wave propagation in tunnel environments. Despite its accuracy, VPE remains computationally intensive for large-scale simulations. Recent advancements have integrated various machine learning techniques to enhance simulation efficiency. The choice of a data processing strategy is crucial, as it determines the perspective from which the model extracts and interprets semantic information, thereby influencing the selection of model architectures. In this paper, we explore the performance of models using different data processing strategies in conjunction with their corresponding network architectures. Specifically, we compare the performance of models applying the cross-section to cross-section strategy, the sliding window strategy, and the sequence to sequence strategy. The experimental results demonstrate that the cross-section to cross-section strategy excels in extrapolation tasks, whereas the sliding window strategy shows superior performance in interpolation tasks.
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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 | 0.001 |
| 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".