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8,280 global cabin abnormal event reports from 2004 to 2024 were used to train a hybrid CNN-LSTM-Attention model for risk classification. The model achieved 95.01% accuracy and an F1 score of 94.17% on its test set. The dataset was authored by Lianbin Zhou and shared on figshare under a CC-BY-4.0 license.
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