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 …
Geopolymer concrete as sustainable material: A state of the art review
The rise in population and improvement in the lifestyle of human beings has caused a rapid
increase in energy demands for buildings in the present day. An upsurge in energy demand …
increase in energy demands for buildings in the present day. An upsurge in energy demand …
[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 …
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 …
Compressive Strength of Fly‐Ash‐Based Geopolymer Concrete by Gene Expression Programming and Random Forest
Fly ash (FA) is a residual from thermal industries that has been effectively utilized in the
production of FA‐based geopolymer concrete (FGPC). To avoid time‐consuming and costly …
production of FA‐based geopolymer concrete (FGPC). To avoid time‐consuming and costly …
Development of deep neural network model to predict the compressive strength of rubber concrete
This paper presents an innovative development process of a Deep Neural Network model to
predict the compressive strength of rubber concrete. To this goal, a rubber concrete …
predict the compressive strength of rubber concrete. To this goal, a rubber concrete …
A systematic review of data science and machine learning applications to the oil and gas industry
This study offered a detailed review of data sciences and machine learning (ML) roles in
different petroleum engineering and geosciences segments such as petroleum exploration …
different petroleum engineering and geosciences segments such as petroleum exploration …
Shallow landslide susceptibility mapping: A comparison between logistic model tree, logistic regression, naïve bayes tree, artificial neural network, and support vector …
Shallow landslides damage buildings and other infrastructure, disrupt agriculture practices,
and can cause social upheaval and loss of life. As a result, many scientists study the …
and can cause social upheaval and loss of life. As a result, many scientists study the …
Predicting compressive strength of manufactured-sand concrete using conventional and metaheuristic-tuned artificial neural network
Y Zhao, H Hu, C Song, Z Wang - Measurement, 2022 - Elsevier
Compressive strength (CS) is the maximum resistance of concrete against axial
compressive loading in standard conditions. Estimation of this parameter is essential for the …
compressive loading in standard conditions. Estimation of this parameter is essential for the …