Ensemble learning models to predict the compressive strength of ...

This study proposes the use of an integrated model to predict the compressive strength of geopolymer concrete.

Currently, single machine learning models are mostly used for predicting the compressive strength of geopolymer concrete, but the use of single models has ...

Ensemble learning based compressive strength prediction ... - Nature

The findings of the analyzed results show that HCVCM-ANFIS outperforms all other ML models to estimate the CS of concrete. HCVCM increases ANFIS ...

To predict the compressive strength of self compacting concrete with ...

This study aims to apply machine learning methods to predict the compression strength of self-compacting recycled aggregate concrete.

An ensemble learning-based prediction model for the compressive ...

This work employs machine learning (ML) to tackle the issue of strength degradation. The analysis considers ten distinct variables linked to concrete ...

An interpretable ensemble learning method to predict the ...

This study explored an optimal method for predicting the compressive strength of concrete based on various ensemble machine learning methods.

Explainable Ensemble Learning and Multilayer Perceptron ... - MDPI

In this study, multilayer perceptron (MLP) and Stacking Regressor, an ensemble machine-learning models, is used to predict the compressive strength of high- ...

Ensemble learning models to predict the compressive strength of ...

Ensemble learning models to predict the compressive strength of geopolymer concrete: a comparative study for geopolymer composition design · Qiong Tian ...

Efficient machine learning models for estimation of compressive ...

Consequently, compressive strength experimentation results and machine learning predictions were compared through statistical methods such as ...

Machine learning and interactive GUI for concrete compressive ...

This study used Machine Learning (ML) models to enhance the prediction of CS, analyzing 1030 experimental CS data ranging from 2.33 to 82.60 MPa from previous ...

Ensemble Machine-Learning-Based Prediction Models for ... - MDPI

Therefore, four different ensemble ML-based algorithms are developed to predict the compressive strength of the RP mortar and the underlining relationship ...

High-performance concrete strength prediction based on ensemble ...

Li and Song [11] used four ensemble learning model algorithms of XGBoost, AdaBoost, GBDT, and RF to construct a model to predict the compressive ...

An ensemble learning-based prediction model for the compressive ...

Super absorbent polymer (SAP) has a capacity to enhance the characteristics of cementitious composites in both their fresh and hardened ...

Ensemble Machine Learning Models to Predict the Compressive ...

Ensemble Machine Learning Models to Predict the Compressive Strength and Ultrasonic Pulse Velocity of Sustainable Concrete.

Enhancing prediction accuracy of concrete compressive strength ...

This study aims to use both standalone and ensemble machine learning techniques to forecast the 28-day compressive strength of high-performance concrete. One ...

Concrete Compressive Strength Prediction by Ensemble Machine ...

This study utilizes ensemble machine-learning techniques, such as Bagging, XGBoost, and Stacking models, to enhance the accuracy of concrete compressive ...

Ensemble learning models to predict the compressive strength of ...

Ensemble learning models to predict the compressive strength of geopolymer concrete: a comparative study for geopolymer composition design.

Predicting concrete compressive strength using hybrid ensembling ...

Semantic Scholar extracted view of "Predicting concrete compressive strength using hybrid ensembling of surrogate machine learning models" by P. G. Asteris ...

Machine learning models for predicting the compressive strength of ...

The present study aims to propose surrogate models based on Support Vector Machine (SVM) and Gaussian Process Regression (GPR) machine learning techniques, ...

Comparison of Machine Learning Techniques for the Prediction of ...

Sayed-Ahmed [16] developed a statistical model to predict compressive strength of concrete containing different matrix mixtures at fixed age ...