A comparative study of four nonlinear dynamic methods and their applications in classification of ship-radiated noise
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Bibliographic record
Abstract
Refined composite multi-scale dispersion entropy (RCMDE), as a new and effective nonlinear dynamic method, has been applied in the field of medical diagnosis and fault diagnosis. In this paper, we first introduce RCMDE into the field of underwater acoustic signal processing for complexity feature extraction of ship radiated noise, and then propose a novel classification method for ship-radiated noise based on RCMDE and k-nearest neighbor (KNN), termed RCMDE-KNN. The results of a comparative experiment show that the proposed RCMDE-KNN classification method can effectively extract the complexity features of ship-radiated noise, and has better classification performance under one and two scales than the other three classification methods based on multi-scale permutation entropy (MPE) and KNN, multi-scale weighted-permutation entropy (MW-PE) and KNN, and multi-scale dispersion entropy (MDE) and KNN, termed MPE-KNN, MW-PE-KNN, and MDE-KNN. It is proved that the RCMDE-KNN classification method for ship-radiated noise is feasible and effective, and can obtain a very high recognition rate.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it