Hybrid CAE-DSVDD for unsupervised vibration-based damage detection in in situ steel truss bridge

Computer Science

• Support Vector 100%
• Data Description 100%
• Deep Autoencoder 100%
• Monitoring Data 66%
• Detection Accuracy 33%
• Class Classification 33%
• Performance Model 33%
• Infrastructure Monitoring 33%
• Effective Solution 33%
• classification approach 33%
• Deep Learning Method 33%
• Autoencoder 33%
• Operational Condition 33%
• Leaning Parameter 33%
• Unsupervised Anomaly Detection 33%
• Input Condition 33%
• Forced Vibration 33%
• Reconstruction Error 33%