Data-driven modeling of mechanical properties of fiber-reinforced concrete: a critical review
Fiber-reinforced concrete (FRC) is extensively used in diverse structural engineering
applications, and its mechanical properties are crucial for designing and evaluating its …
applications, and its mechanical properties are crucial for designing and evaluating its …
[HTML][HTML] Machine learning-based seismic response and performance assessment of reinforced concrete buildings
F Kazemi, N Asgarkhani, R Jankowski - Archives of Civil and Mechanical …, 2023 - Springer
Complexity and unpredictability nature of earthquakes makes them unique external loads
that there is no unique formula used for the prediction of seismic responses. Hence, this …
that there is no unique formula used for the prediction of seismic responses. Hence, this …
LCA of municipal wastewater treatment
Wastewater treatment plants play a significant role in minimizing environmental pollution by
treating wastewater and reducing the release of contaminants into the environment …
treating wastewater and reducing the release of contaminants into the environment …
Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
One of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the
ability to anticipate their flexural response. With a comprehensive grid search, several …
ability to anticipate their flexural response. With a comprehensive grid search, several …
Spatiotemporal heterogeneity of ecosystem service interactions and their drivers at different spatial scales in the Yellow River Basin
Q Liu, J Qiao, M Li, M Huang - Science of The Total Environment, 2024 - Elsevier
Accurately understanding ecosystem service (ES) interactions and an analysis of the
complex, multiscale driving mechanisms are foundational prerequisites for implementing …
complex, multiscale driving mechanisms are foundational prerequisites for implementing …
A systematic review of deep learning approaches for surface defect detection in industrial applications
Detecting surface defects plays a crucial role in ensuring the quality, functionality, and
security of the production process. Traditional image processing techniques and machine …
security of the production process. Traditional image processing techniques and machine …
[HTML][HTML] Energy consumption prediction in water treatment plants using deep learning with data augmentation
Wastewater treatment plants (WWTPs) are energy-intensive facilities that play a critical role
in meeting stringent effluent quality regulations. Accurate prediction of energy consumption …
in meeting stringent effluent quality regulations. Accurate prediction of energy consumption …
Hybrid machine learning models for prediction of daily dissolved oxygen
Measuring water quality parameters is a significant step in many hydrological assessments.
Dissolved oxygen (DO) is one of these parameters that is an indicator of water quality …
Dissolved oxygen (DO) is one of these parameters that is an indicator of water quality …
[HTML][HTML] Machine learning for an explainable cost prediction of medical insurance
Predictive modeling in healthcare continues to be an active actuarial research topic as more
insurance companies aim to maximize the potential of Machine Learning (ML) approaches …
insurance companies aim to maximize the potential of Machine Learning (ML) approaches …
Machine learning-based prediction of preplaced aggregate concrete characteristics
Abstract Preplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse
aggregate is placed in the mold and a Portland cement-sand grout with admixtures is …
aggregate is placed in the mold and a Portland cement-sand grout with admixtures is …