Hassan Sarmadi
Hassan Sarmadi
Co-Founder and Head of Research & Development at IPESFP Startup Company
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Citata da
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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
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
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
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
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
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
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
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
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
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
Application of supervised learning to validation of damage detection
H Sarmadi, A Entezami
Archive of Applied Mechanics 91, 393–410, 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
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
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
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
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
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
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
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
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
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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