Large‐scale structural health monitoring using composite recurrent neural networks and grid environments

Author:

Eltouny Kareem A.1,Liang Xiao1

Affiliation:

1. Department of Civil, Structural and Environmental Engineering University at Buffalo Buffalo NY 14260 USA

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Graphics and Computer-Aided Design,Computer Science Applications,Civil and Structural Engineering,Building and Construction

Reference73 articles.

1. Abadi M. Agarwal A. Barham P. Brevdo E. Chen Z. Citro C. Corrado G. S. Davis A. Dean J. Devin M. Ghemawat S. Goodfellow I. Harp A. Irving G. Isard M. Jia Y. Jozefowicz R. Kaiser L. Kudlur M. …Zheng X.(2016).Tensorflow: Large‐scale machine learning on heterogeneous distributed systems. InProceedings of the 12th USENIX Conference on Operating Systems Design and Implementation(pp. 265–283). USENIX Association.

2. 1-D CNNs for structural damage detection: Verification on a structural health monitoring benchmark data

3. Alves V. Cury A. Roitman N. Magluta C. &Cremona C.(2015).Structural modification assessment using supervised learning methods applied to vibration data.Engineering Structures 99 439–448.

4. Wireless smart sensors for monitoring the health condition of civil infrastructure;Amezquita‐Sanchez J.;Scientia Iranica,2018

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