Comments: Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms

Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms

Artificial intelligence algorithms have recently demonstrated their efficacy in accurately predicting concrete properties by optimizing mixing proportions and overcoming design limitations. In this regard, foam concrete (FC) production presents a unique challenge, necessitating extensive experimenta...

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Bibliographic Details
Main Authors:	Abdellatief M., Wong L.S., Din N.M., Mo K.H., Ahmed A.N., El-Shafie A.
Other Authors:	57855303900
Format:	Article
Published:	Elsevier Ltd 2025
Subjects:	Cements Concrete aggregates Concrete mixing Forecasting Learning algorithms Machine learning Mean square error Multilayer neural networks Parameter estimation Regression analysis Sensitivity analysis Artificial intelligence algorithms Compressive strength prediction- parametric analyse Foam concretes Gaussian process regression Input variables Machine learning algorithms Parametric analysis Regression algorithms Strength prediction Support vector regressions Compressive strength
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Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms

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