Cargando…
Damage Detection in Largely Unobserved Structures under Varying Environmental Conditions: An AutoRegressive Spectrum and Multi-Level Machine Learning Methodology
Vibration-based damage detection in civil structures using data-driven methods requires sufficient vibration responses acquired with a sensor network. Due to technical and economic reasons, it is not always possible to deploy a large number of sensors. This limitation may lead to partial information...
Autores principales: | Entezami, Alireza, Mariani, Stefano, Shariatmadar, Hashem |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8963060/ https://www.ncbi.nlm.nih.gov/pubmed/35214303 http://dx.doi.org/10.3390/s22041400 |
Ejemplares similares
-
Mendelian randomization: the challenge of unobserved environmental confounds
por: Koellinger, Philipp D, et al.
Publicado: (2019) -
A Graph Feature Auto-Encoder for the prediction of unobserved node features on biological networks
por: Hasibi, Ramin, et al.
Publicado: (2021) -
Is the Effect of Environmental Attitudes on Behavior Driven Solely by Unobserved Heterogeneity?
por: Andersen, Henrik Kenneth, et al.
Publicado: (2022) -
Uncertain regression model with autoregressive time series errors
por: Chen, Dan
Publicado: (2021) -
Message Passing-Based Inference for Time-Varying Autoregressive Models
por: Podusenko, Albert, et al.
Publicado: (2021)