A systematic review of optimization algorithms for structural health monitoring and optimal sensor placement

S Hassani, U Dackermann - Sensors, 2023 - mdpi.com
In recent decades, structural health monitoring (SHM) has gained increased importance for
ensuring the sustainability and serviceability of large and complex structures. To design an …

[HTML][HTML] Review on smartphone sensing technology for structural health monitoring

H Sarmadi, A Entezami, KV Yuen, B Behkamal - Measurement, 2023 - Elsevier
Sensing is a critical and inevitable sector of structural health monitoring (SHM). Recently,
smartphone sensing technology has become an emerging, affordable, and effective system …

HECON: Weight assessment of the product loyalty criteria considering the customer decision's halo effect using the convolutional neural networks

G Haseli, R Ranjbarzadeh, M Hajiaghaei-Keshteli… - Information …, 2023 - Elsevier
The economic pressures and increasing competition in markets have led to the CEOs of
companies being forced to make the right strategic decisions in the development of products …

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 …

An IoT based authentication system for therapeutic herbs measured by local descriptors using machine learning approach

S Roopashree, J Anitha, TR Mahesh, VV Kumar… - Measurement, 2022 - Elsevier
The work aims to develop an automatic recognition model to classify medicinal plants using
machine learning techniques to enrich the traditional medical system of India. Though many …

A locally unsupervised hybrid learning method for removing environmental effects under different measurement periods

MH Daneshvar, H Sarmadi, KV Yuen - Measurement, 2023 - Elsevier
Environmental effects induce deceptive variability in unlabeled vibration data for structural
health monitoring (SHM). Although unsupervised learning is an effective solution to this …

Machine learning in safety and health research: a scientometric analysis

KH Abdullah, D Sofyan - International Journal of Information Science and …, 2023 - ijism.isc.ac
Safety and health are intricately interwoven and have become indispensable to the thriving
business world and anthropology. It is concerned with ensuring employees' physical …

Develo** a digital twin model for monitoring building structural health by combining a building information model and a real-scene 3D model

J Xu, X Shu, P Qiao, S Li, J Xu - Measurement, 2023 - Elsevier
Structural health monitoring (SHM) is a critical component of ensuring the safety of buildings,
yet the effective management of sensors and their corresponding monitoring data is …

The state of the art of artificial intelligence approaches and new technologies in structural health monitoring of bridges

R Zinno, SS Haghshenas, G Guido, K Rashvand… - Applied Sciences, 2022 - mdpi.com
The challenges of urban administration are growing, as the population, automobiles, and
cities rise. Making cities smarter is thus one of the most effective solutions to urban issues. A …

Investigation of temperature effects into long-span bridges via hybrid sensing and supervised regression models

B Behkamal, A Entezami, C De Michele, AN Arslan - Remote Sensing, 2023 - mdpi.com
Temperature is an important environmental factor for long-span bridges because it induces
thermal loads on structural components that cause considerable displacements, stresses …