.png){kind=icon}
.png){kind=icon}
Return
Unified damage detection in heterogeneous bridges: A framework based on LSTM residuals and record-level aggregation
.png){kind=icon}
PRE
AI
Y
DOI：10.1016/j.asoc.2026.116190.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• A unified framework for bridge damage detection is proposed with three stages. • An LightGBM classifier is employed for damage diagnosis. • The framework is validated in two lab datasets and a real-world bridge dataset. • The model provides efficiently scalable data-driven damage monitoring systems.
Journal
IF:
6.6
Papers:
1.4W
Citations:
4.8W
Organization
No organization information available
Cited Papers