Modelling the abrasion resistance of self-consolidating concrete

This work aimed to model the abrasion resistance of self-consolidating concretes (SCCs) utilising artificial neural networks (ANNs) and to compare their prediction performances with those of traditional regression models. To do this, 12 SCC mixtures were made with different mixture proportions and their abrasion depths were measured every 30 s for a testing period of 20 min. Several ANN and regression models were developed by varying a number of independent variables, the number of neurons, regression functions and samples allotted for training and testing. The results of the study revealed the superior performance of the neural network models compared with the regression models. The ANN models showed satisfactory performance in predicting the abrasion depth of SCCs, particularly when testing samples were chosen from data inside the boundaries of mixture proportions and abrasion depths. Prediction errors increased when mixtures with the highest and lowest abrasion depths were selected as testing mixtures....

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