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 …
A review on material mix proportion and strength influence parameters of geopolymer concrete: Application of ANN model for GPC strength prediction
Concrete is a combination of cement, sand, aggregate, and water. Cement manufacturing
causes the generation of various gases, mainly greenhouse gases like CO 2 in the …
causes the generation of various gases, mainly greenhouse gases like CO 2 in the …
Data-driven shear strength prediction of steel fiber reinforced concrete beams using machine learning approach
The incorporation of steel fibers in a concrete mix enhances the shear capacity of reinforced
concrete beams and a comprehensive understanding of this phenomenon is imperative to …
concrete beams and a comprehensive understanding of this phenomenon is imperative to …
Compressive strength prediction of eco-efficient GGBS-based geopolymer concrete using GEP method
Geopolymer concrete (GPC) could be used as an environmental-friendly alternative solution
for concrete production due to the detrimental impacts of cement production on the …
for concrete production due to the detrimental impacts of cement production on the …
[HTML][HTML] Compressive strength of concrete containing furnace blast slag; optimized machine learning-based models
Abstract Replacing Ordinary Portland Cement (OPC) with industrial waste like Ground
Granulated Blast Furnace Slag (GGBFS) has been proven to have remarkable benefits …
Granulated Blast Furnace Slag (GGBFS) has been proven to have remarkable benefits …
Investigation of performance metrics in regression analysis and machine learning-based prediction models
Performance metrics (Evaluation metrics or error metrics) are crucial components of
regression analysis and machine learning-based prediction models. A performance metric …
regression analysis and machine learning-based prediction models. A performance metric …
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 …
[HTML][HTML] Sustainable cement replacement using waste eggshells: A review on mechanical properties of eggshell concrete and strength prediction using artificial neural …
Abstract Though the European Commission classifies eggshell as a hazardous material,
using eggshell powder in place of cement can aid in waste reduction and contribute to …
using eggshell powder in place of cement can aid in waste reduction and contribute to …
Predicting compressive strength of concrete containing recycled aggregate using modified ANN with different optimization algorithms
Using recycled aggregate in concrete is one of the best ways to reduce construction
pollution and prevent the exploitation of natural resources to provide the needed aggregate …
pollution and prevent the exploitation of natural resources to provide the needed aggregate …
Prediction of the residual flexural strength of fiber reinforced concrete using artificial neural networks
The work in hand proposes Artificial Neural Networks (ANN) to predict the residual strength
of fiber reinforced concrete under bending load. A database containing experimental and …
of fiber reinforced concrete under bending load. A database containing experimental and …