Predictive models for concrete properties using machine learning and deep learning approaches: A review

MM Moein, A Saradar, K Rahmati… - Journal of Building …, 2023 - Elsevier
Concrete is one of the most widely used materials in various civil engineering applications.
Its global production rate is increasing to meet demand. Mechanical properties of concrete …

A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications

O Avci, O Abdeljaber, S Kiranyaz, M Hussein… - Mechanical systems and …, 2021 - Elsevier
Monitoring structural damage is extremely important for sustaining and preserving the
service life of civil structures. While successful monitoring provides resolute and staunch …

Applications of artificial intelligence for disaster management

W Sun, P Bocchini, BD Davison - Natural Hazards, 2020 - Springer
Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …

Machine learning for risk and resilience assessment in structural engineering: Progress and future trends

X Wang, RK Mazumder, B Salarieh… - Journal of Structural …, 2022 - ascelibrary.org
Population growth, economic development, and rapid urbanization in many areas have led
to increased exposure and vulnerability of structural and infrastructure systems to hazards …

Vibration-based damage detection techniques used for health monitoring of structures: a review

S Das, P Saha, SK Patro - Journal of Civil Structural Health Monitoring, 2016 - Springer
Structural health monitoring (SHM) techniques have been studied for several years. An
effective approach for SHM is to choose the parameters that are sensitive to the damage …

Fuzzy C-means (FCM) clustering algorithm: a decade review from 2000 to 2014

J Nayak, B Naik, HS Behera - … Intelligence in Data Mining-Volume 2 …, 2015 - Springer
The Fuzzy c-means is one of the most popular ongoing area of research among all types of
researchers including Computer science, Mathematics and other areas of engineering, as …

Unsupervised learning methods for data-driven vibration-based structural health monitoring: a review

K Eltouny, M Gomaa, X Liang - Sensors, 2023 - mdpi.com
Structural damage detection using unsupervised learning methods has been a trending
topic in the structural health monitoring (SHM) research community during the past decades …

Eliminating environmental and operational effects on structural modal frequency: A comprehensive review

Z Wang, DH Yang, TH Yi, GH Zhang… - Structural Control and …, 2022 - Wiley Online Library
Modal frequencies are widely used for vibration‐based structural health monitoring (SHM)
and for capturing the dynamics of a monitored structure to reveal possible failures. However …

Artificial intelligence and structural health monitoring of bridges: A review of the state-of-the-art

R Zinno, SS Haghshenas, G Guido, A VItale - IEEE Access, 2022 - ieeexplore.ieee.org
In the age of the smart city, things like the Internet of Things (IoT) and big data analytics are
making big changes to the way traditional structural health monitoring (SHM) is done. Also …

Bayesian‐optimized unsupervised learning approach for structural damage detection

KA Eltouny, X Liang - Computer‐Aided Civil and Infrastructure …, 2021 - Wiley Online Library
Structural health monitoring (SHM) is developing rapidly to fulfill the world's need for resilient
and sustainable communities. Due to the current advancements in machine learning and …