Machine Learning in Fly Ash Concrete Compressive Strength Prediction
摘要
In this paper, machine leaning systems are used to perform a prediction task of the fly ash concrete compressive strength. As most related literatures have used a conventional backpropagation neural network for predicting the concrete strength we aim to use another machine learning system; named Radial basis function network to perform this prediction task. Moreover, a comparison of the aforementioned network with the backpropagation neural network is proposed in term of accuracy, mean square error reached, and training time.