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Preprints
, 2025, Deep Learning Approaches for Classifying Aviation Safety Incidents: Evidence from Australian Data, http://dx.doi.org/10.20944/preprints202508.2196.v1
, 2025, Exploring Aviation Incident Narratives Using Topic Modeling and Clustering Techniques, http://dx.doi.org/10.48550/arxiv.2501.07924
, 2025, Natural Language Processing and Deep Learning Models to Classify Phase of Flight in Aviation Safety Occurrences, http://dx.doi.org/10.48550/arxiv.2501.06564
, 2025, Sequential Classification of Aviation Safety Occurrences with Natural Language Processing, http://dx.doi.org/10.48550/arxiv.2501.06490
, 2025, Applications of natural language processing in aviation safety: A review and qualitative analysis, http://dx.doi.org/10.48550/arxiv.2501.06210
, 2025, Comparative Analysis of Topic Modeling Techniques on ATSB Text Narratives Using Natural Language Processing, http://dx.doi.org/10.48550/arxiv.2501.01227
, A Multi-Head Attention-Based Transformer Model for Predicting Causes in Aviation Incident, http://dx.doi.org/10.20944/preprints202502.1196.v1
, Does the Choice of Topic Modeling Technique Impact the Interpretation of Aviation Incident Reports? A Methodological Assessment, http://dx.doi.org/10.20944/preprints202503.2171.v1
, Explainable Supervised Learning Models for Aviation Predictions in Australia, http://dx.doi.org/10.20944/preprints202502.0998.v1
, Natural Language Processing for Aviation Safety: Predicting Injury Levels from Incident Reports in Australia, http://dx.doi.org/10.20944/preprints202503.2251.v1
, Semantic Topic Modeling of Aviation Safety Reports: A Comparative Analysis Using BERTopic and PLSA, http://dx.doi.org/10.20944/preprints202505.1509.v1