Hadi Salehi
Cited by
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Emerging artificial intelligence methods in structural engineering
H Salehi, R Burgueño
Engineering structures 171, 170-189, 2018
Machine learning framework for predicting failure mode and shear capacity of ultra high performance concrete beams
R Solhmirzaei, H Salehi, V Kodur, MZ Naser
Engineering structures 224, 111221, 2020
Integrated structural health monitoring in bridge engineering
Z He, W Li, H Salehi, H Zhang, H Zhou, P Jiao
Automation in construction 136, 104168, 2022
Genetic programming in civil engineering: advent, applications and future trends
Q Zhang, K Barri, P Jiao, H Salehi, AH Alavi
Artificial Intelligence Review 54, 1863-1885, 2021
A comprehensive review of self-powered sensors in civil infrastructure: State-of-the-art and future research trends
H Salehi, R Burgueño, S Chakrabartty, N Lajnef, AH Alavi
Engineering Structures 234, 111963, 2021
Data mining methodology employing artificial intelligence and a probabilistic approach for energy-efficient structural health monitoring with noisy and delayed signals
H Salehi, S Das, S Biswas, R Burgueño
Expert Systems with Applications 135, 259-272, 2019
Towards packet-less ultrasonic sensor networks for energy-harvesting structures
S Das, H Salehi, Y Shi, S Chakrabartty, R Burgueno, S Biswas
Computer Communications 101, 94-105, 2017
Structural assessment and damage identification algorithms using binary data
H Salehi, S Das, S Chakrabartty, S Biswas, R Burgueño
Smart Materials, Adaptive Structures and Intelligent Systems 57304, V002T05A011, 2015
Structural damage identification using image‐based pattern recognition on event‐based binary data generated from self‐powered sensor networks
H Salehi, S Das, S Chakrabartty, S Biswas, R Burgueño
Structural Control and Health Monitoring 25 (4), e2135, 2018
Data interpretation framework integrating machine learning and pattern recognition for self-powered data-driven damage identification with harvested energy variations
H Salehi, S Biswas, R Burgueño
Engineering Applications of Artificial Intelligence 86, 136-153, 2019
Damage identification in aircraft structures with self‐powered sensing technology: A machine learning approach
H Salehi, S Das, S Chakrabartty, S Biswas, R Burgueño
Structural Control and Health Monitoring 25 (12), e2262, 2018
Machine learning-driven assessment of fire-induced concrete spalling of columns
MZ Naser, H Salehi
ACI Materials Journal 117 (6), 7-16, 2020
A machine-learning approach for damage detection in aircraft structures using self-powered sensor data
H Salehi, S Das, S Chakrabartty, S Biswas, R Burgueño
Sensors and smart structures technologies for civil, mechanical, and …, 2017
Structural health monitoring from discrete binary data through pattern recognition
H Salehi, R Burgueño, S Das, S Biswas, S Chakrabartty
Insights and Innovations in Structural Engineering, Mechanics and …, 2016
Seismic protection of vulnerable equipment with semi-active control by employing robust and clipped-optimal algorithms
H Salehi, T Taghikhany, A Yeganeh Fallah
International Journal of Civil Engineering 12 (4), 413-428, 2014
Predicting flexural capacity of ultrahigh-performance concrete beams: machine learning–based approach
R Solhmirzaei, H Salehi, V Kodur
Journal of Structural Engineering 148 (5), 04022031, 2022
Data-driven failure prediction in brittle materials: A phase field-based machine learning framework
EAB de Moraes, H Salehi, M Zayernouri
Journal of Machine Learning for Modeling and Computing 2 (1), 2021
An algorithmic framework for reconstruction of time-delayed and incomplete binary signals from an energy-lean structural health monitoring system
H Salehi, S Das, S Chakrabartty, S Biswas, R Burgueño
Engineering Structures 180, 603-620, 2019
Application of robust-optimum algorithms in semi-active control strategy for seismic protection of equipment
H Salehi, T Taghikhany
15th World Conference on Earthquake Engineering, Sep, 24-28, 2012
Localized damage identification in plate-like structures using self-powered sensor data: A pattern recognition strategy
H Salehi, S Chakrabartty, S Biswas, R Burgueno
Measurement 135, 23-38, 2019
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