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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 …
Prediction of mechanical properties of high‐performance concrete and ultrahigh‐performance concrete using soft computing techniques: A critical review
A cement‐based material that meets the general goals of mechanical properties, workability,
and durability as well as the ever‐increasing demands of environmental sustainability is …
and durability as well as the ever‐increasing demands of environmental sustainability is …
A modified firefly algorithm-artificial neural network expert system for predicting compressive and tensile strength of high-performance concrete
The compressive and tensile strength of high-performance concrete (HPC) is a highly
nonlinear function of its constituents. The significance of expert frameworks for predicting the …
nonlinear function of its constituents. The significance of expert frameworks for predicting the …
Evaluation of geopolymer concrete at high temperatures: An experimental study using machine learning
M Rahmati, V Toufigh - Journal of Cleaner Production, 2022 - Elsevier
Studying the mechanical performance of concrete after being exposed to high temperatures
is an important step in the damage assessment of buildings and fire safety applications …
is an important step in the damage assessment of buildings and fire safety applications …
Data-driven machine learning approach for exploring and assessing mechanical properties of carbon nanotube-reinforced cement composites
Traditional experimental investigation on the mechanical properties of cement composites is
deprecated due to the intensive time and labor involved. Existing predictive models can …
deprecated due to the intensive time and labor involved. Existing predictive models can …
Interpretable machine-learning models for maximum displacements of RC beams under impact loading predictions
The estimation of the maximum displacements of RC beams subjected to impact loads is of
pivotal importance to define demand models to be employed in structural design. The …
pivotal importance to define demand models to be employed in structural design. The …
Prediction of fresh and hardened properties of self-compacting concrete using support vector regression approach
This article presents the feasibility of using support vector regression (SVR) technique to
determine the fresh and hardened properties of self-compacting concrete. Two different …
determine the fresh and hardened properties of self-compacting concrete. Two different …
A novel support vector regression (SVR) model for the prediction of splice strength of the unconfined beam specimens
Splice strength in reinforced concrete is an important parameter for the safe design of any
structure which should be assessed with ease and accuracy. Analytically the assessment of …
structure which should be assessed with ease and accuracy. Analytically the assessment of …
Integrating machine learning and response surface methodology for analyzing anisotropic mechanical properties of biocomposites
S Saravanakumar, S Sathiyamurthy… - Composite …, 2024 - Taylor & Francis
This study enhances the anisotropic mechanical properties of banana fiber-epoxy
composites by optimizing fiber loading, orientation, and treatment using Response Surface …
composites by optimizing fiber loading, orientation, and treatment using Response Surface …
Machine-learning-based models to predict shear transfer strength of concrete joints
In predicting the shear transfer strength (STS) of concrete joints, numerous design
parameters need to be considered due to diverse application scenarios and various …
parameters need to be considered due to diverse application scenarios and various …