NEURAL NETWORKS FOR PREDICTING PROPERTIES OF CONCRETES WITH ADMIXTURES

By Wps Dias, S. P. Pooliyadda. 2001

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Modeling compressive strength of recycled aggregate concrete by Artificial Neural Network, Model Tree and Non-linear Regression (2014, methodology): “ANN models were developed to predict the strength and slump of ready mixed concrete and high strength concrete, in which chemical admixtures and or mineral additives were used (Dias and Pooliyadda, 2001; I-Cheng, 2007).”
Computational design optimization of concrete mixtures: A review (2018, methodology): “Since then, researchers have applied ANN methods to wide-ranging problems in cement and concrete research; they have been used to model several types of concrete properties, including compressive strength, slump, filling capacity, and segregation and for many types of concrete including high perform”
Prediction of self-compacting concrete strength using artificial neural networks (2016, methodology): “…concerning the application of ANNs for the prediction of the compressive strength and modulus of elasticity (Atici, 2011; Cladera & Marí, 2004; Dias & Pooliyadda, 2001; González-Taboada, GonzálezFonteboa, Martínez-Abella, & Pérez-Ordóñez, 2016; Kostić & Vasović, 2015; Lee, 2003; Sonebi &…”