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 …
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 …
Torsional capacity evaluation of RC beams using an improved bird swarm algorithm optimised 2D convolutional neural network
This study presents the application of deep learning technology in torsional capacity
evaluation of reinforced concrete (RC) beams. A data-driven model based on 2D …
evaluation of reinforced concrete (RC) beams. A data-driven model based on 2D …
Back-propagation neural network optimized by K-fold cross-validation for prediction of torsional strength of reinforced Concrete beam
Due to the limitation of sample size in predicting the torsional strength of Reinforced
Concrete (RC) beams, this paper aims to discuss the feasibility of employing a novel …
Concrete (RC) beams, this paper aims to discuss the feasibility of employing a novel …
Shear strength prediction of reinforced concrete beams using machine learning
Recent years have witnessed a surge in the application of machine learning techniques for
solving hard to solve structural engineering problems. The application of machine learning …
solving hard to solve structural engineering problems. The application of machine learning …
Recent trends in prediction of concrete elements behavior using soft computing (2010–2020)
Soft computing (SC), due to its high abilities to solve the complex problems with uncertainty
and multiple parameters, has been widely investigated and used, especially in structural …
and multiple parameters, has been widely investigated and used, especially in structural …
Axial compressive strength predictive models for recycled aggregate concrete filled circular steel tube columns using ANN, GEP, and MLR
In recent years, recycled aggregate concrete (RAC) has been used as a suitable solution to
solve the problems related to the disposal of construction waste and contribute to …
solve the problems related to the disposal of construction waste and contribute to …
Predicting shear strength of FRP-reinforced concrete beams using novel synthetic data driven deep learning
Abstract Machine learning algorithms have emerged as a powerful technique to predict the
engineering properties of composite materials and structures where traditional statistical …
engineering properties of composite materials and structures where traditional statistical …
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 …
Flexural strength prediction for concrete beams reinforced with FRP bars using gene expression programming
FRP bars have been recently used as an alternative to the traditional steel bars in
construction, especially in harsh environmental regions. Gene expression programming …
construction, especially in harsh environmental regions. Gene expression programming …