Predicting the compressive strength and slump of high strength concrete using neural network

By A. Öztas, Murat Pala, E. Özbay, E. Kanca, Naci Çagˇlar, M. A. Bhatti. 2006

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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 compressive strength of concrete containing construction and demolition waste using artificial neural networks (2013, methodology): “Some studies have been published, showing that ANN can model complex and nonlinear relationships between parameters affecting the compressive strength of concrete [10–17], the compressive strength of high strength concrete [18], the compressive strength”
Prediction of the strength of mineral admixture concrete using multivariable regression analysis and an artificial neural network (2011, methodology): “This time-consuming procedure results in the wastage of material and increased cost of concrete production (Oztas et al., 2006).”