[HTML][HTML] Application of Multivariate Adaptive Regression Splines (MARS) approach in prediction of compressive strength of eco-friendly concrete
Concrete is the most often used material in the building sector. The use of ground-
granulated blast-furnace slag (GGBFS) and recycled concrete aggregates (RCA) in concrete …
granulated blast-furnace slag (GGBFS) and recycled concrete aggregates (RCA) in concrete …
Establishing efficacy of machine learning techniques for vulnerability information of tubular buildings
During recent times, the emergence of artificial intelligence in structural engineering has
rendered researchers to work on reducing the overall computational effort required for …
rendered researchers to work on reducing the overall computational effort required for …
An extra tree regression model for discharge coefficient prediction: novel, practical applications in the hydraulic sector and future research directions
Despite modern advances used to estimate the discharge coefficient (Cd), it is still a major
challenge for hydraulic engineers to accurately determine Cd for side weirs. In this study …
challenge for hydraulic engineers to accurately determine Cd for side weirs. In this study …
Acoustic emission and artificial intelligence procedure for crack source localization
The acoustic emission (AE) technique is one of the most widely used in the field of structural
monitoring. Its popularity mainly stems from the fact that it belongs to the category of non …
monitoring. Its popularity mainly stems from the fact that it belongs to the category of non …
[HTML][HTML] A hybrid data-driven and metaheuristic optimization approach for the compressive strength prediction of high-performance concrete
Compressive strength determination of high-performance concrete (HPC) is necessary for its
practical usage. However, experimental testing for this purpose is resource intensive and …
practical usage. However, experimental testing for this purpose is resource intensive and …
Generalized uncertainty in surrogate models for concrete strength prediction
Applied soft computing has been widely used to predict material properties, optimal mixture,
and failure modes. This is challenging, especially for the highly nonlinear behavior of brittle …
and failure modes. This is challenging, especially for the highly nonlinear behavior of brittle …
[HTML][HTML] Prediction of pull-out behavior of timber glued-in glass fiber reinforced polymer and steel rods under various environmental conditions based on ANN and …
This study employs soft computing techniques, including artificial neural network (ANN)
models and gene expression programming (GEP), to enhance the prediction of ultimate load …
models and gene expression programming (GEP), to enhance the prediction of ultimate load …
Prediction of high-performance concrete compressive strength using deep learning techniques
Concrete compressive strength (CCS) is the most crucial structural engineering designing
conventional concrete and high-performance concrete (HPC) structures. Accurately …
conventional concrete and high-performance concrete (HPC) structures. Accurately …
Inflow forecasting using regularized extreme learning machine: Haditha reservoir chosen as case study
For effective water resource management, water budgeting, and optimal release discharge
from a reservoir, the accurate prediction of daily inflow is critical. An attempt has been made …
from a reservoir, the accurate prediction of daily inflow is critical. An attempt has been made …
[HTML][HTML] Optimized artificial neural network model for accurate prediction of compressive strength of normal and high strength concrete
This study develops and presents an Artificial Neural Network (ANN) model employing the
Levenberg-Marquardt Backpropagation (LMBP) training algorithm to predict the …
Levenberg-Marquardt Backpropagation (LMBP) training algorithm to predict the …