신경망기법을 사용한 콘크리트의 배합요소 추정

Prediction on the Proportioning of Concrete Mixes Using Neural Network

Concrete mix proportioning is a process of selecting the right combination of many materials such as cement, fine aggregates, coarse aggregates, water, and admixtures to make concrete satisfying for specification and cost. In determining proportioning of concrete mixes, code information, specification, and the experience of experts are needed. However, all factors regarding mix proportioning factor cannot be considered. Therefore, the final acceptance depends on concrete quality control test results. The proportioning of concrete mixes and the adjustments are somewhat complicated, time-consuming, and uncertain tasks. In this paper, as a tool to predict the factor of the proportioning of concrete mixes, an artificial neural network is used. To consider the varieties of material properties, the standard mixed table of two companies of ready mixed concrete are used. The results show that neural net works is successfully applied to the prediction of concrete mix proportioning factor.