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[HTML][HTML] Synthesis, properties, applications, 3D printing and machine learning of graphene quantum dots in polymer nanocomposites
This comprehensive review discusses the recent progress in synthesis, properties,
applications, 3D printing and machine learning of graphene quantum dots (GQDs) in …
applications, 3D printing and machine learning of graphene quantum dots (GQDs) in …
[HTML][HTML] A research agenda for augmented and virtual reality in architecture, engineering and construction
This paper presents a study on the usage landscape of augmented reality (AR) and virtual
reality (VR) in the architecture, engineering and construction sectors, and proposes a …
reality (VR) in the architecture, engineering and construction sectors, and proposes a …
Advances in computational intelligence of polymer composite materials: machine learning assisted modeling, analysis and design
The superior multi-functional properties of polymer composites have made them an ideal
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
Determining the critical risk factors for predicting the severity of ship collision accidents using a data-driven approach
H Lan, X Ma, W Qiao, W Deng - Reliability Engineering & System Safety, 2023 - Elsevier
Ship collision accidents often result in serious casualties and property losses. Predicting the
severity of ship collisions is beneficial to improve maritime transport safety. Therefore, this …
severity of ship collisions is beneficial to improve maritime transport safety. Therefore, this …
Grey wolf optimizer-based machine learning algorithm to predict electric vehicle charging duration time
Precise charging time prediction can effectively mitigate the inconvenience to drivers
induced by inevitable charging behavior throughout trips. Although the effectiveness of the …
induced by inevitable charging behavior throughout trips. Although the effectiveness of the …
[HTML][HTML] Enhancing construction safety: Machine learning-based classification of injury types
The construction industry is a hazardous industry with significant injuries and fatalities. Few
studies have used data-driven analysis to investigate injuries due to construction accidents …
studies have used data-driven analysis to investigate injuries due to construction accidents …
Application of machine learning techniques for predicting the consequences of construction accidents in China
R Zhu, X Hu, J Hou, X Li - Process Safety and Environmental Protection, 2021 - Elsevier
Construction accidents can easily cause massive casualties and property losses. This
research uses machine learning technique to analyze 16 critical factors and assess the …
research uses machine learning technique to analyze 16 critical factors and assess the …
Integrating feature engineering, genetic algorithm and tree-based machine learning methods to predict the post-accident disability status of construction workers
The construction industry is among the riskiest industries around the world. Hence, the
preliminary studies exploring the consequences of occupational accidents have received …
preliminary studies exploring the consequences of occupational accidents have received …
RFCNN: Traffic accident severity prediction based on decision level fusion of machine and deep learning model
Traffic accidents on highways are a leading cause of death despite the development of traffic
safety measures. The burden of casualties and damage caused by road accidents is very …
safety measures. The burden of casualties and damage caused by road accidents is very …
Scenario-based automated data preprocessing to predict severity of construction accidents
Occupational accidents are common in the construction industry, therefore develo**
prediction models to detect high severe accidents would be useful. However, existing …
prediction models to detect high severe accidents would be useful. However, existing …