딥러닝 알고리즘 기반 탄산화 진행 예측에서 활성화 함수 적용에 관한 기초적 연구

A Fundamental Study on the Effect of Activation Function in Predicting Carbonation Progress Using Deep Learning Algorithm

Concrete carbonation is one of the factors that reduce the durability of concrete. In modern times, due to industrialization, the carbon dioxide concentration in the atmosphere is increasing, and the impact of carbonation is increasing. So, it is important to understand the carbonation resistance according to the concrete compounding to secure the concrete durability life. In this study, we want to predict the concrete carbonation velocity coefficient, which is an indicator of the carbonation resistance of concrete, through the deep learning algorithm, and to find the activation function suitable for the prediction of carbonation rate coefficient as a process to determine the learning accuracy through the deep learning algorithm. In the scope of this study, using the ReLU function showed better accuracy than using other activation functions.