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Saeed Eftekhar Azam

As seen in: MDPI
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Articles

Leveraging Deep Learning for Robust Structural Damage Detection and Classification: A Transfer Learning Approach via CNN

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By Burak Duran, Saeed Eftekhar Azam, Masoud Sanayei, Eftekhar Azam
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Novel Physics-Informed Artificial Neural Network Architectures for System and Input Identification of Structural Dynamics PDEs

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By Sarvin Moradi, Burak Duran, Saeed Eftekhar Azam, Massood Mofid
| MDPI
3.1.1. System Identification In the first step, the capability of the PINN in system identification is evaluated. Since the ANN is not capable of parameter prediction, only the PINN’s estimates are presented in this section. To train the PINN, the analytical displacement of the SDOF was contaminated with an additive zero-mean white Gaussian noise which its Root Mean Square (RMS) was 1% of the RMS of the signal, and it was fed into the PINN during three natural periods.
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