Prediction of compressive strength of concrete containing construction and demolition waste using artificial neural networks

被引:227
作者
Abdon Dantas, Adriana Trocoli [1 ]
Leite, Monica Batista [1 ]
Nagahama, Koji de Jesus [1 ]
机构
[1] State Univ Feira de Santana, Dept Technol, BR-44036900 Feira De Santana, BA, Brazil
关键词
Recycled concrete; Compressive strength; Artificial neural networks; SILICA FUME; FLY-ASH; AGGREGATE; SLUMP;
D O I
10.1016/j.conbuildmat.2012.09.026
中图分类号
TU [建筑科学];
学科分类号
081407 [建筑环境与能源工程];
摘要
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. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:717 / 722
页数:6
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