Experimental machine learning approach for building structural health monitoring application
- DOI
- 10.1088/1742-6596/2647/18/182031
- Published
- 2024-06-01
- Container
- Journal of Physics: Conference Series
- Publisher
- IOP Publishing
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1088/1742-6596/2647/18/182031,
title = {Experimental machine learning approach for building structural health monitoring application},
author = {Mohamed Oualid Mghazli and Zineb Zoubir and Antoine Rallu and Nouzha Lamdouar and Mohamed Elmankibi},
year = {2024},
journal = {Journal of Physics: Conference Series},
doi = {10.1088/1742-6596/2647/18/182031},
url = {https://doi.org/10.1088/1742-6596/2647/18/182031}
}RIS
TY - JOUR TI - Experimental machine learning approach for building structural health monitoring application AU - Mohamed Oualid Mghazli AU - Zineb Zoubir AU - Antoine Rallu AU - Nouzha Lamdouar AU - Mohamed Elmankibi PY - 2024 JO - Journal of Physics: Conference Series DO - 10.1088/1742-6596/2647/18/182031 UR - https://doi.org/10.1088/1742-6596/2647/18/182031 ER -
APA
Mghazli, M. O., Zoubir, Z., Rallu, A., Lamdouar, N., & Elmankibi, M. (2024). Experimental machine learning approach for building structural health monitoring application. Journal of Physics: Conference Series. https://doi.org/10.1088/1742-6596/2647/18/182031
Source records
- crossref · retrieved 2026-09-26T11:56:23.290Z