Journal
CONSTRUCTION AND BUILDING MATERIALS
Volume 38, Issue -, Pages 717-722Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.conbuildmat.2012.09.026
Keywords
Recycled concrete; Compressive strength; Artificial neural networks
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Funding
- CAPES [PE170/2008]
- FAPESB
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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.
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