Deep attention SMOTE: Data augmentation with a learnable interpolation factor for imbalanced anomaly detection of gas turbines

• Published in: Computers in industry Vol. 151; p. 103972
• Main Authors: Liu, Dan, Zhong, Shisheng, Lin, Lin, Zhao, Minghang, Fu, Xuyun, Liu, Xueyun
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.10.2023
• Subjects: Anomaly detection; Data augmentation; Gas turbine; Imbalanced data; Inter-class overlap; Inter-class overlap; Imbalanced data; Data augmentation; Gas turbine; Anomaly detection

Anomaly detection of gas turbines faces the significant challenges of data imbalance and inter-class overlap. In this paper, we develop a novel data augmentation method, namely deep attention synthetic minority over-sampling technique with the Encoder-Decoder (DA-SMOTE-ED), which serves as a key ste...