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
Pages
6
From page
717
To page
722
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
Serial Year
2013
Journal title
Construction and Building Materials
Record number
1634523
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