Reliability of probabilistic numerical data for training machine learning algorithms to detect damage in bridges.
- Published in:
- Structural Control & Health Monitoring, 2022, v. 29, n. 7, p. 1, doi. 10.1002/stc.2950
- By:
- Publication type:
- Article
Works by Figueiredo, Eloi
Results: 14
1
2
Damage‐sensitive feature extraction with stacked autoencoders for unsupervised damage detection.
- Published in:
- Structural Control & Health Monitoring, 2021, v. 28, n. 5, p. 1, doi. 10.1002/stc.2714
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- Publication type:
- Article
3
Bayesian data-driven framework for structural health monitoring of composite structures under limited experimental data.
- Published in:
- Structural Health Monitoring, 2025, v. 24, n. 2, p. 738, doi. 10.1177/14759217241236801
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- Publication type:
- Article
4
Damage quantification using transfer component analysis combined with Gaussian process regression.
- Published in:
- Structural Health Monitoring, 2023, v. 22, n. 2, p. 1290, doi. 10.1177/14759217221094500
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- Publication type:
- Article
5
Three decades of statistical pattern recognition paradigm for SHM of bridges.
- Published in:
- Structural Health Monitoring, 2022, v. 21, n. 6, p. 3018, doi. 10.1177/14759217221075241
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- Publication type:
- Article
6
Deep principal component analysis: An enhanced approach for structural damage identification.
- Published in:
- Structural Health Monitoring, 2019, v. 18, n. 5/6, p. 1444, doi. 10.1177/1475921718799070
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- Publication type:
- Article
7
A global expectation-maximization based on memetic swarm optimization for structural damage detection.
- Published in:
- Structural Health Monitoring, 2016, v. 15, n. 5, p. 610, doi. 10.1177/1475921716654433
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- Publication type:
- Article
8
Machine learning algorithms for damage detection under operational and environmental variability.
- Published in:
- Structural Health Monitoring, 2011, v. 10, n. 6, p. 559, doi. 10.1177/1475921710388971
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- Publication type:
- Article
9
Influence of the Autoregressive Model Order on Damage Detection.
- Published in:
- Computer-Aided Civil & Infrastructure Engineering, 2011, v. 26, n. 3, p. 225, doi. 10.1111/j.1467-8667.2010.00685.x
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- Publication type:
- Article
10
Genetic-based EM algorithm to improve the robustness of Gaussian mixture models for damage detection in bridges.
- Published in:
- Structural Control & Health Monitoring, 2017, v. 24, n. 3, p. n/a, doi. 10.1002/stc.1886
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- Publication type:
- Article
11
A structural decomposition approach for detecting, locating, and quantifying nonlinearities in chain-like systems.
- Published in:
- Structural Control & Health Monitoring, 2010, v. 17, n. 7, p. 761, doi. 10.1002/stc.396
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- Publication type:
- Article
12
A Comprehensive Study on Unsupervised Transfer Learning for Structural Health Monitoring of Bridges Using Joint Distribution Adaptation.
- Published in:
- Infrastructures, 2024, v. 9, n. 8, p. 131, doi. 10.3390/infrastructures9080131
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- Publication type:
- Article
13
Transfer Learning for Structural Health Monitoring in Bridges That Underwent Retrofitting.
- Published in:
- Buildings (2075-5309), 2023, v. 13, n. 9, p. 2323, doi. 10.3390/buildings13092323
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- Publication type:
- Article
14
Smartphone Application for Structural Health Monitoring of Bridges.
- Published in:
- Sensors (14248220), 2022, v. 22, n. 21, p. 8483, doi. 10.3390/s22218483
- By:
- Publication type:
- Article