A novel anomaly detection method based on adaptive Mahalanobis-squared distance and one-class kNN rule for structural health monitoring under environmental effects H Sarmadi, A Karamodin Mechanical Systems and Signal Processing 140, 106495, 2020 | 210 | 2020 |
Big data analytics and structural health monitoring: a statistical pattern recognition-based approach A Entezami, H Sarmadi, B Behkamal, S Mariani Sensors 20 (8), 2328, 2020 | 114 | 2020 |
Ensemble learning‐based structural health monitoring by Mahalanobis distance metrics H Sarmadi, A Entezami, B Saeedi Razavi, KV Yuen Structural Control and Health Monitoring 28, e2663, 2021 | 87 | 2021 |
Early damage detection by an innovative unsupervised learning method based on kernel null space and peak‐over‐threshold H Sarmadi, KV Yuen Computer‐Aided Civil and Infrastructure Engineering 36, 1150– 1167, 2021 | 79 | 2021 |
Unsupervised learning-based damage assessment of full-scale civil structures under long-term and short-term monitoring MH Daneshvar, H Sarmadi Engineering Structures 256, 114059, 2022 | 64 | 2022 |
Bridge health monitoring in environmental variability by new clustering and threshold estimation methods H Sarmadi, A Entezami, M Salar, C De Michele Journal of Civil Structural Health Monitoring 11, 629–644, 2021 | 62 | 2021 |
Structural health monitoring by a novel probabilistic machine learning method based on extreme value theory and mixture quantile modeling H Sarmadi, KV Yuen Mechanical Systems and Signal Processing 173, 109049, 2022 | 58 | 2022 |
Structural damage detection by a new iterative regularization method and an improved sensitivity function A Entezami, H Shariatmadar, H Sarmadi Journal of Sound and Vibration 399, 285-307, 2017 | 52 | 2017 |
A novel data-driven method for structural health monitoring under ambient vibration and high-dimensional features by robust multidimensional scaling A Entezami, H Sarmadi, M Salar, C De Michele, AN Arslan Structural Health Monitoring 20 (5), 2758-2777, 2021 | 50 | 2021 |
Application of supervised learning to validation of damage detection H Sarmadi, A Entezami Archive of Applied Mechanics 91, 393–410, 2020 | 46 | 2020 |
Energy-based damage localization under ambient vibration and non-stationary signals by ensemble empirical mode decomposition and Mahalanobis-squared distance H Sarmadi, A Entezami, M Daneshvar Khorram Journal of Vibration and Control 26 (11-12), 1012-1027, 2020 | 46 | 2020 |
A new iterative model updating technique based on least squares minimal residual method using measured modal data H Sarmadi, A Karamodin, A Entezami Applied Mathematical Modelling 40 (23-24), 10323-10341, 2016 | 46 | 2016 |
Long-term health monitoring of concrete and steel bridges under large and missing data by unsupervised meta learning A Entezami, H Sarmadi, B Behkamal Engineering Structures 279, 115616, 2023 | 42 | 2023 |
An innovative hybrid strategy for structural health monitoring by modal flexibility and clustering methods A Entezami, H Sarmadi, B Saeedi Razavi Journal of Civil Structural Health Monitoring 10 (5), 845-859, 2020 | 42 | 2020 |
A sensitivity‐based finite element model updating based on unconstrained optimization problem and regularized solution methods M Rezaiee‐Pajand, A Entezami, H Sarmadi Structural Control and Health Monitoring 27 (5), e2481, 2020 | 42 | 2020 |
A novel double-hybrid learning method for modal frequency-based damage assessment of bridge structures under different environmental variation patterns A Entezami, H Sarmadi, B Behkamal Mechanical Systems and Signal Processing 201, 110676, 2023 | 38 | 2023 |
On model‑based damage detection by an enhanced sensitivity function of modal flexibility and LSMR‑Tikhonov method under incomplete noisy modal data H Sarmadi, A Entezami, M Ghalehnovi Engineering with Computers 38, 111-127, 2022 | 38 | 2022 |
Damage identification of structural systems by modal strain energy and an optimization-based iterative regularization method MH Daneshvar, M Saffarian, H Jahangir, H Sarmadi Engineering with Computers 39 (3), 2067-2087, 2023 | 37 | 2023 |
Investigation of machine learning methods for structural safety assessment under variability in data: Comparative studies and new approaches H Sarmadi Journal of Performance of Constructed Facilities 35 (6), 04021090, 2021 | 37 | 2021 |
Probabilistic data self-clustering based on semi-parametric extreme value theory for structural health monitoring H Sarmadi, A Entezami, C De Michele Mechanical Systems and Signal Processing 187, 109976, 2023 | 33 | 2023 |