Deep neural network with high-order neuron for the prediction of foamed concrete strength

Abstract

The article presents a deep neural network model for the prediction of the compressive strength of foamed concrete. A new, high-order neuron was developed for the deep neural network model to improve the performance of the model. Moreover, the cross-entropy cost function and rectified linear unit activation function were employed to enhance the performance of the model. The present model was then applied to predict the compressive strength of foamed concrete through a given data set, and the obtained results were compared with other machine learning methods including conventional artificial neural network (C-ANN) and second-order artificial neural network (SO-ANN). To further validate the pr..