Prediction of rubberized mortar properties using artificial neural network and fuzzy logic

In this study, waste rubberized aggregates were used as sand in mortar production which had two different sizes in the range of diameter (0–1) and (1–4) mm. Flexural strength and compressive strength of mortar were determined experimentally for waste rubberized aggregates mortar types. The experimental results showed that the flexural and compressive strength decreases considerably when amount of waste rubber aggregates used in the mixtures increases. Experimental results were also obtained by constructing models according to artificial neural network and fuzzy logic methods. It is concluded that the properties of waste rubberized mortar can be obtained without any experimental tests when the artificial neural network and fuzzy logic models results are discussed. It is seen that training and testing results are similar to the experimental results.