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 …
Predictive models for concrete properties using machine learning and deep learning approaches: A review
Concrete is one of the most widely used materials in various civil engineering applications.
Its global production rate is increasing to meet demand. Mechanical properties of concrete …
Its global production rate is increasing to meet demand. Mechanical properties of concrete …
[HTML][HTML] A novel approach to explain the black-box nature of machine learning in compressive strength predictions of concrete using Shapley additive explanations …
Abstract Machine learning (ML) techniques are often employed for the accurate prediction of
the compressive strength of concrete. Despite higher accuracy, previous ML models failed to …
the compressive strength of concrete. Despite higher accuracy, previous ML models failed to …
Machine learning prediction of mechanical properties of concrete: Critical review
Accurate prediction of the mechanical properties of concrete has been a concern since
these properties are often required by design codes. The emergence of new concrete …
these properties are often required by design codes. The emergence of new concrete …
Comparative study of advanced computational techniques for estimating the compressive strength of UHPC
The effect of raw materials on the compressive strength of concrete is a complex process,
especially in the case of ultra-high-performance concrete (UHPC), where a higher number of …
especially in the case of ultra-high-performance concrete (UHPC), where a higher number of …
A novel hybrid extreme learning machine–grey wolf optimizer (ELM-GWO) model to predict compressive strength of concrete with partial replacements for cement
Compressive strength of concrete is one of the most determinant parameters in the design of
engineering structures. This parameter is generally determined by conducting several tests …
engineering structures. This parameter is generally determined by conducting several tests …
A comparative study of random forest and genetic engineering programming for the prediction of compressive strength of high strength concrete (HSC)
Supervised machine learning and its algorithm is an emerging trend for the prediction of
mechanical properties of concrete. This study uses an ensemble random forest (RF) and …
mechanical properties of concrete. This study uses an ensemble random forest (RF) and …
Hybrid machine learning model and Shapley additive explanations for compressive strength of sustainable concrete
Y Wu, Y Zhou - Construction and Building Materials, 2022 - Elsevier
The application of the traditional support vector regression (SVR) model to predict the
compressive strength of concrete faces the challenge of parameter tuning. To this end, a …
compressive strength of concrete faces the challenge of parameter tuning. To this end, a …
A novel approach to predict shear strength of tilted angle connectors using artificial intelligence techniques
Shear connectors play a prominent role in the design of steel-concrete composite systems.
The behavior of shear connectors is generally determined through conducting push-out …
The behavior of shear connectors is generally determined through conducting push-out …
Developing hybrid ELM-ALO, ELM-LSO and ELM-SOA models for predicting advance rate of TBM
Accurate prediction of TBM performance is very important for efficient completion of TBM
construction tunnel project. This paper aims to predict the advance rate (AR) of tunnel boring …
construction tunnel project. This paper aims to predict the advance rate (AR) of tunnel boring …