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Masonry Compressive Strength Prediction Using Artificial Neural Networks [PDF]
, 2019 The masonry is not only included among the oldest building materials, but it is also the most widely used material due to its simple construction and low cost compared to the other modern building materials. Nevertheless, there is not yet a robust quantitative method, available in the literature, which can reliably predict its strength, based on the ...
Asteris, Panagiotis G. +6 more
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Dimension Analysis-Based Model for Prediction of Shale Compressive Strength
Advances in Materials Science and Engineering, 2016 The compressive strength of shale is a comprehensive index for evaluating the shale strength, which is linked to shale well borehole stability. Based on correlation analysis between factors (confining stress, height/diameter ratio, bedding angle, and ...
Xiangyu Fan +6 more
doaj +1 more source
Scientific Reports, 2022 Predicting the compressive strength of concrete is a complicated process due to the heterogeneous mixture of concrete and high variable materials. Researchers have predicted the compressive strength of concrete for various mixes using machine learning ...
Vimal Rathakrishnan +2 more
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A hybrid strategy of AutoML and SHAP for automated and explainable concrete strength prediction
Case Studies in Construction Materials, 2023 The precise prediction of concrete compressive strength is essential for ensuring safe and reliable infrastructure design and construction. However, traditional empirical models often struggle to accurately predict compressive strength due to the complex
Bochao Sun +4 more
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Compressive Strength Prediction of Fly Ash Concrete Using Machine Learning Techniques
Buildings, 2022 It is time-consuming and uneconomical to estimate the strength properties of fly ash concrete using conventional compression experiments. For this reason, four machine learning models—extreme learning machine, random forest, original support vector ...
Yimin Jiang, Hangyu Li, Yisong Zhou
semanticscholar +1 more source
The Scientific World Journal, 2014 Understanding of the compressive strength of concrete is important for activities like construction arrangement, prestressing operations, and proportioning new mixtures and for the quality assurance.
Naresh Kumar Nagwani, Shirish V. Deo
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Shock and Vibration, 2021 Cemented tailings backfill is widely used in worldwide mining areas, and its development trend is increasing due to the technical and economic benefits. However, there is no reliable and simple machine learning model for the prediction of the compressive
Qi-Ang Wang, Jia Zhang, Jiandong Huang
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Prediction of Concrete Compressive Strength in Saline Soil Environments
Materials, 2022 Saline soil in Western China contains high concentrations of chloride ions, sulfate ions, and other corrosive ions, and the performance of concrete will substantially deteriorate from exposure to this environment. Therefore, it is of great significance to study and predict the concrete compressive strength in saline soil environments.
Deqiang Yang +4 more
openaire +2 more sources
Sustainability, 2020 This study aims to analyze the sensitivity and robustness of two Artificial Intelligence (AI) techniques, namely Gaussian Process Regression (GPR) with five different kernels (Matern32, Matern52, Exponential, Squared Exponential, and Rational Quadratic ...
D. Dao +6 more
semanticscholar +1 more source
Recycled Aggregates Concrete Compressive Strength Prediction Using Artificial Neural Networks (ANNs)
Infrastructures, 2021 The recycled aggregate is an alternative with great potential to replace the conventional concrete alongside with other benefits such as minimising the usage of natural resources in exploitation to produce new conventional concrete. Eventually, this will
Mohamad Ali Ridho B K A +3 more
semanticscholar +1 more source