Machine learning for structural engineering: A state-of-the-art review
HT Thai - Structures, 2022 - Elsevier
Abstract Machine learning (ML) has become the most successful branch of artificial
intelligence (AI). It provides a unique opportunity to make structural engineering more …
intelligence (AI). It provides a unique opportunity to make structural engineering more …
Error metrics and performance fitness indicators for artificial intelligence and machine learning in engineering and sciences
Artificial intelligence (AI) and Machine learning (ML) train machines to achieve a high level
of cognition and perform human-like analysis. Both AI and ML seemingly fit into our daily …
of cognition and perform human-like analysis. Both AI and ML seemingly fit into our daily …
Artificial intelligence, machine learning, and deep learning in structural engineering: a scientometrics review of trends and best practices
Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are emerging
techniques capable of delivering elegant and affordable solutions which can surpass those …
techniques capable of delivering elegant and affordable solutions which can surpass those …
[HTML][HTML] A comprehensive overview of jute fiber reinforced cementitious composites
H Song, J Liu, K He, W Ahmad - Case Studies in Construction Materials, 2021 - Elsevier
Natural fibers are eco-friendly, cost-effective, lightweight, renewable, have better thermal
properties and corrosion resistance capabilities. The addition of natural fibers in …
properties and corrosion resistance capabilities. The addition of natural fibers in …
Prediction of biodiesel production from microalgal oil using Bayesian optimization algorithm-based machine learning approaches
N Sultana, SMZ Hossain, M Abusaad, N Alanbar… - Fuel, 2022 - Elsevier
Biodiesel has appeared as a renewable and clean energy resource and a means of
diminishing global warming. This study provides Bayesian optimization algorithm (BOA) …
diminishing global warming. This study provides Bayesian optimization algorithm (BOA) …
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 …
Predicting load capacity of shear walls using SVR–RSM model
Accurate prediction of the shear capacity of reinforced concrete shear walls (RCSW) is
essential for the wind and seismic design of buildings. However, due to the diverse structural …
essential for the wind and seismic design of buildings. However, due to the diverse structural …
Machine learning application to predict the Mechanical properties of Glass Fiber mortar
In this study, the mechanical properties of glass fiber mortars have been predicted using
machine learning tools, Response Surface Methodology (RSM), and Artificial Neural …
machine learning tools, Response Surface Methodology (RSM), and Artificial Neural …
Bayesian optimization algorithm based support vector regression analysis for estimation of shear capacity of FRP reinforced concrete members
The use of fiber-reinforced polymer (FRP) rebars in lieu of steel rebars has led to some
deviations in the shear behavior of concrete members. Several methods have been …
deviations in the shear behavior of concrete members. Several methods have been …
Modeling and multi-objective optimization of microalgae biomass production and CO2 biofixation using hybrid intelligence approaches
This study investigates the impacts of temperature, light-dark cycles (LD), and nitrogen-
phosphorus ratios (NP) on Chlorella vulgaris microalgae biomass productivity (BP) and CO …
phosphorus ratios (NP) on Chlorella vulgaris microalgae biomass productivity (BP) and CO …