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18 July 2025

Correction: Moradi et al. Novel Physics-Informed Artificial Neural Network Architectures for System and Input Identification of Structural Dynamics PDEs. Buildings 2023, 13, 650

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1
Department of Civil Engineering, University of Tehran, Tehran P.O. Box 14155-6619, Iran
2
Department of Civil and Environmental Engineering, University of New Hampshire, Durham, NH 03824, USA
3
Department of Civil Engineering, Sharif University of Technology, Tehran P.O. Box 11365-11155, Iran
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Author to whom correspondence should be addressed.
This article belongs to the Special Issue Structural Identification and Damage Evaluation by Integrating Physics-Based Models with Data

Affiliation Update

In the published publication [], there was an error regarding the affiliation for Sarvin Moradi. The updated affiliation should be Department of Civil Engineering, University of Tehran, Tehran P.O. Box 14155-6619, Iran. The authors state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.

Reference

  1. Moradi, S.; Duran, B.; Eftekhar Azam, S.; Mofid, M. Novel Physics-Informed Artificial Neural Network Architectures for System and Input Identification of Structural Dynamics PDEs. Buildings 2023, 13, 650. [Google Scholar] [CrossRef]
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