Ruhua Wang
- (2024): Structural damage identification by using physics-guided residual neural networks. Dans: Engineering Structures, v. 318 (novembre 2024).
- (2023): A novel transformer-based semantic segmentation framework for structural condition assessment. Dans: Structural Health Monitoring, v. 23, n. 2 (juillet 2023).
- (2022): Structural damage quantification using ensemble‐based extremely randomised trees and impulse response functions. Dans: Structural Control and Health Monitoring, v. 29, n. 10 (13 septembre 2022).
- (2021): Densely connected convolutional networks for vibration based structural damage identification. Dans: Engineering Structures, v. 245 (octobre 2021).
- (2021): Deep residual network framework for structural health monitoring. Dans: Structural Health Monitoring, v. 20, n. 4 (avril 2021).
- (2017): Development and application of a deep learning–based sparse autoencoder framework for structural damage identification. Dans: Structural Health Monitoring, v. 18, n. 1 (décembre 2017).
- (2021): Development and application of random forest technique for element level structural damage quantification. Dans: Structural Control and Health Monitoring, v. 28, n. 3 (5 février 2021).
Structurae coopère avec
