Modeling of Porous Concrete Mixing Plan using Artificial Neural Network

Concrete is the most widely used material in the construction industry of the country. Porous concrete has always been the focus of researchers due to its special properties such as high permeability. The present article has determined the design of porous concrete mix with specific strength based on the laboratory program and modeling by using artificial neural network. The experiment program in this research started with 200 mixing plans in the field of porous cylindrical concrete and preparing a database and it was modeled by using different types of multilayer perceptron neural network (MLP). Evaluation indices including regression coefficient and mean square error have been used to check the efficiency of artificial neural network structures. The results showed that the regression coefficient in most of the structures used was above 85% and in the neural network with the optimal structure it was 95%. Also, the evaluated error index in the neural network with optimal structure is determined to be 0.121.