Uso de las redes neuronales artificiales en el modelado del ensayo de resistencia a compresión de concreto de construcción según la norma ASTM C39/C 39M

Abstract

Two artificial neural network models for predicting the results of compressive strength test of a construction concrete after the curing period are proposed. The compressive strength of concrete is one of the most important variables in its quality control. However, these tests are carried out after a period of curing so results of the test are not immediately available. Therefore a reliable mathematical model that would obtain the test results immediately after the curing time These models present correlation coefficients higher than 0.9 and allow reducing the time to obtain the results of compressive strength tests.