Title of article :
Prediction of compressive strength of concrete containing construction and demolition waste using artificial neural networks
Author/Authors :
Dantas، نويسنده , , Adriana Trocoli Abdon and Batista Leite، نويسنده , , Mônica and de Jesus Nagahama، نويسنده , , Koji، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2013
Abstract :
In this study Artificial Neural Networks (ANNs) models were developed for predicting the compressive strength, at the age of 3, 7, 28 and 91 days, of concretes containing Construction and Demolition Waste (CDW). The experimental results used to construct the models were gathered from literature. A total of 1178 data was used for modeling ANN, 77.76% in the training phase, and 22.24% in the testing phase. To construct the model, 17 input parameters were used to achieve one output parameter, referred to as the compressive strength of concrete containing CDW. The results obtained in both, the training and testing phases strongly show the potential use of ANN to predict 3, 7, 28 and 91 days compressive strength of concretes containing CDW.
Keywords :
Artificial neural networks , Recycled concrete , Compressive strength
Journal title :
Construction and Building Materials
Journal title :
Construction and Building Materials