Prediction of Compressive Strength of Concrete in Wet-Dry Environment by BP Artificial Neural Networks
Open Access
- 2 April 2018
- journal article
- research article
- Published by Hindawi Limited in Advances in Materials Science and Engineering
- Vol. 2018, 1-11
- https://doi.org/10.1155/2018/6204942
Abstract
Engineering structure degradation in the marine environment, especially the tidal zone and splash zone, is serious. The compressive strength of concrete exposed to the wet-dry cycle is investigated in this study. Several significant influencing factors of compressive strength of concrete in the wet-dry environment are selected. Then, the database of compressive strength influencing factors is established from vast literature after a statistical analysis of those data. Backpropagation artificial neural networks (BP-ANNs) are applied to establish a multifactorial model to predict the compressive strength of concrete in the wet-dry exposure environment. Furthermore, experiments are done to verify the generalization of the BP-ANN model. This model turns out to give a high accuracy and statistical analysis to confirm some rules in marine concrete mix and exposure. In general, this model is practical to predict the concrete mechanical performance.Keywords
Funding Information
- National Program on Key Basic Research Project of China (2015CB6551002)
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