16 citations · 36 across the 10 of their papers we have counts for
10 papers
Classification of Operational Records in Aviation Using Deep Learning Approaches
Aziida Nanyonga, Graham Wild
Ensuring safety in the aviation industry is critical, even minor anomalies can lead to severe consequences. This study evaluates the performance of four different models for DP (de…
Phase of Flight Classification in Aviation Safety using LSTM, GRU, and BiLSTM: A Case Study with ASN Dataset
Aziida Nanyonga, Hassan Wasswa, Graham Wild
Safety is the main concern in the aviation industry, where even minor operational issues can lead to serious consequences. This study addresses the need for comprehensive aviation…
Exploring Aviation Incident Narratives Using Topic Modeling and Clustering Techniques
Aziida Nanyonga, Hassan Wasswa, Ugur Turhan +2
Aviation safety is a global concern, requiring detailed investigations into incidents to understand contributing factors comprehensively. This study uses the National Transportatio…
Aviation Safety Enhancement via NLP & Deep Learning: Classifying Flight Phases in ATSB Safety Reports
Aziida Nanyonga, Hassan Wasswa, Graham Wild
Aviation safety is paramount, demanding precise analysis of safety occurrences during different flight phases. This study employs Natural Language Processing (NLP) and Deep Learnin…
Natural Language Processing and Deep Learning Models to Classify Phase of Flight in Aviation Safety Occurrences
Aziida Nanyonga, Hassan Wasswa, Oleksandra Molloy +2
The air transport system recognizes the criticality of safety, as even minor anomalies can have severe consequences. Reporting accidents and incidents play a vital role in identify…
Sequential Classification of Aviation Safety Occurrences with Natural Language Processing
Aziida Nanyonga, Hassan Wasswa, Ugur Turhan +2
Safety is a critical aspect of the air transport system given even slight operational anomalies can result in serious consequences. To reduce the chances of aviation safety occurre…