Machine learning in manufacturing ergonomics: Recent advances, challenges, and opportunities

S Lee, L Liu, R Radwin, J Li - IEEE Robotics and Automation …, 2021 - ieeexplore.ieee.org
The rapid development of machine learning (ML) technology has introduced substantial
impact on ergonomics research in manufacturing. Numerous studies and practices have …

Soft computing applications in the field of human factors and ergonomics: A review of the past decade of research

E Çakıt, W Karwowski - Applied Ergonomics, 2024 - Elsevier
The main objectives of this study were to 1) review the literature on the applications of soft
computing concepts to the field of human factors and ergonomics (HFE) between 2013 and …

Prediction of construction accident outcomes based on an imbalanced dataset through integrated resampling techniques and machine learning methods

K Koc, Ö Ekmekcioğlu, AP Gurgun - Engineering, Construction and …, 2022 - emerald.com
Purpose Central to the entire discipline of construction safety management is the concept of
construction accidents. Although distinctive progress has been made in safety management …

Develo** an ensemble predictive safety risk assessment model: case of Malaysian construction projects

H Sadeghi, SR Mohandes, MR Hosseini… - International journal of …, 2020 - mdpi.com
Occupational Health and Safety (OHS)-related injuries are vexing problems for construction
projects in develo** countries, mostly due to poor managerial-, governmental-, and …

Performance optimization of integrated resilience engineering and lean production principles

A Azadeh, R Yazdanparast, SA Zadeh… - Expert Systems with …, 2017 - Elsevier
This paper conducts performance assessment from integrated resilience engineering (IRE)
and lean production points of view. This is the first study that evaluates the impact of …

An intelligent framework to assess and improve operating room performance considering ergonomics

F Azizi, M Hamid, B Salimi, M Rabbani - Expert Systems with Applications, 2023 - Elsevier
Operating rooms (ORs) are one of the most stressful and complex work environments, and
the surgical staff are highly exposed to ergonomic problems. In addition, the satisfaction of …

A neuro-fuzzy risk prediction methodology for falling from scaffold

M Jahangiri, HRJ Solukloei, M Kamalinia - Safety science, 2019 - Elsevier
Fall from height is one of the most significant safety issues in the construction industry, due
to the high number of fatal injuries. Scaffolds are a leading cause and have one of the …

Performance assessment and improvement of a care unit for COVID-19 patients with resilience engineering and motivational factors: An artificial neural network …

Z Mehdizadeh-Somarin, B Salimi… - Computers in Biology …, 2022 - Elsevier
The global conflict with the new coronavirus disease (COVID-19) has led to frequent visits to
hospitals and medical centers. This significant increase in visits can be severely detrimental …

An intelligent algorithm to evaluate and improve the performance of a home healthcare center considering trust indicators

SA Torabzadeh, R Tavakkoli-Moghaddam… - Computers in Biology …, 2022 - Elsevier
Home healthcare (HHC) is a beneficial choice for many people and especially an essential
alternative to clinics and hospitals for infection prevention during the COVID-19 pandemic …

[HTML][HTML] Generating a landslide susceptibility map using integrated meta-heuristic optimization and machine learning models

T Bostan - Sustainability, 2024 - mdpi.com
A landslide susceptibility assessment is one of the critical steps in planning for landslide
disaster prevention. Advanced machine learning methods can be used as data-driven …