- Systematic multiscale models to predict the compressive strength of ...🔍
- Systematic Multiscale Models to Predict the Compressive Strength of ...🔍
- Soft computing techniques🔍
- Systematic multiscale models to predict the🔍
- Systematic|multiscale|models|to|predict|the|compressive|strength ...🔍
- Ensemble learning models to predict the compressive strength of ...🔍
- Soft Computing and Machine Learning|Based Models to Predict the ...🔍
- Sustainability|driven model for predicting compressive strength in ...🔍
Systematic multiscale models to predict the compressive strength of ...
Systematic multiscale models to predict the compressive strength of ...
In this study, Linear (LR), Non-Linear (NLR), and Multi-logistic (MLR) regression models were used to develop the predictive models for estimating the ...
Systematic Multiscale Models to Predict the Compressive Strength of ...
This study compares the strength of preferentially replaced cement pastes with microsilica (MS) and nanosilica (NS) incorporation by proposing several ...
Systematic multiscale models to predict the compressive strength of ...
This study aims to establish systematic multiscale models to predict the compressive strength of concrete mixes containing a high volume of fly ash (HVFA)
Systematic multiscale models to predict the compressive strength of ...
The most important parameters which affects the compressive strength of FA-GPC mixtures according to this model are the curing temperature and sodium silicate ...
Systematic multiscale models to predict the compressive strength of ...
In this study, three different models including the linear relationship model (LR), nonlinear model (NLR), and multi-logistic model (MLR) were proposed to ...
Soft computing techniques: Systematic multiscale models to predict ...
The sensitivity investigation concludes that the curing time is the most dominating parameter for the prediction of the compressive strength of HVFA concrete ...
Systematic multiscale models to predict the compressive strength of ...
Fig 15. Residual error diagram of compressive strength of fly ash-based geopolymer concrete mixtures using training, testing, and validating dataset for all ...
Systematic multiscale models to predict the - ProQuest
[...]achieving an authoritative model for predicting the compressive strength of geopolymer concrete is necessary regarding saving time, energy, and cost- ...
Systematic multiscale models to predict the compressive strength of ...
Systematic multiscale models to predict the compressive strength of self-compacting concretes modified with nanosilica at different curing ages · Abstract.
Systematic-multiscale-models-to-predict-the-compressive-strength ...
Systematic multiscale models to predict the compressive strength of self-compacting concretes modified with nanosilica at different curing ...
Systematic Multiscale Models to Predict the Compressive Strength of ...
Systematic Multiscale Models to Predict the Compressive Strength of Cement Paste as a Function of Microsilica and Nanosilica Contents, Water/Cement Ratio ...
Systematic Multiscale Models to Predict the Compressive Strength of ...
In this process, the compressive strength of cement paste modified with NS and MS was modeled using four different models, including the Linear Regression Model ...
Systematic multiscale models to predict the compressive strength of ...
Semantic Scholar extracted view of "Soft computing techniques: Systematic multiscale models to predict the compressive strength of HVFA concrete based on ...
Systematic multiscale models to predict the compressive strength of ...
Therefore, achieving an authoritative model for predicting the compressive strength of geopolymer concrete is necessary regarding saving time, energy, and cost- ...
Systematic multiscale models to predict the compressive strength of ...
Systematic multiscale models to predict the compressive strength of fly ash-based geopolymer concrete at various mixture proportions and curing regimes.
Systematic multiscale models to predict the compressive strength of ...
In this study, three different models including the linear relationship model (LR), nonlinear model (NLR), and multi-logistic model (MLR) were ...
Systematic multiscale models to predict the compressive strength of ...
TL;DR: In this paper, the compressive strength of fly ash-based geopolymer concrete (FA-GPC) is estimated using linear, non-linear and multi-logistic regression ...
Ensemble learning models to predict the compressive strength of ...
Systematic multiscale models to predict the compressive strength of fly ash-based geopolymer concrete at various mixture proportions and ...
Soft Computing and Machine Learning-Based Models to Predict the ...
The Multi-Linear Regression model can predict the compressive strength and slump flow diameter of the fly ash-modified self-compacted concrete with different ...
Sustainability-driven model for predicting compressive strength in ...
This study proposes a mathematical model for predicting compressive strength (CS), aiming to further the objective of designing sustainable concretes.