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Structural health monitoring by a novel probabilistic machine learning method based on extreme value theory and mixture quantile modeling Journal article
Mechanical Systems and Signal Processing, 2022,Volume: 173
Authors:  Sarmadi, Hassan;  Yuen, Ka Veng
Favorite |  | TC[WOS]:9 TC[Scopus]:9 | Submit date:2022/05/13
Generalized Extreme Value  Machine Learning  Mixture Quantile  Probabilistic Anomaly Detection  Structural Health Monitoring  Threshold Estimation  
Early damage detection by an innovative unsupervised learning method based on kernel null space and peak-over-threshold Journal article
Computer-Aided Civil and Infrastructure Engineering, 2021,Volume: 36,Issue: 9,Page: 1150-1167
Authors:  Sarmadi, Hassan;  Yuen, Ka Veng
Favorite |  | TC[WOS]:29 TC[Scopus]:33 | Submit date:2021/12/08
Ensemble learning-based structural health monitoring by Mahalanobis distance metrics Journal article
Structural Control and Health Monitoring, 2020,Volume: 28,Issue: 2
Authors:  Hassan Sarmadi;  Alireza Entezami;  Behzad Saeedi Razavi;  Ka-Veng Yuen
Favorite |  | TC[WOS]:33 TC[Scopus]:41 | Submit date:2021/03/09
Damage Detection  Ensemble Learning  Environmental Variability  Mahalanobis Distance  Structural Health Monitoring  Unsupervised Learning