![](/images/graphics-bg.png)
Prediction of Compressive Strength of Concrete in Wet-Dry Environment by BP Artificial Neural Networks
Joint Authors
Liang, Chengyao
Qian, Chunxiang
Chen, Huaicheng
Kang, Wence
Source
Advances in Materials Science and Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-04-02
Country of Publication
Egypt
No. of Pages
11
Abstract EN
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.
American Psychological Association (APA)
Liang, Chengyao& Qian, Chunxiang& Chen, Huaicheng& Kang, Wence. 2018. Prediction of Compressive Strength of Concrete in Wet-Dry Environment by BP Artificial Neural Networks. Advances in Materials Science and Engineering،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1121327
Modern Language Association (MLA)
Liang, Chengyao…[et al.]. Prediction of Compressive Strength of Concrete in Wet-Dry Environment by BP Artificial Neural Networks. Advances in Materials Science and Engineering No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1121327
American Medical Association (AMA)
Liang, Chengyao& Qian, Chunxiang& Chen, Huaicheng& Kang, Wence. Prediction of Compressive Strength of Concrete in Wet-Dry Environment by BP Artificial Neural Networks. Advances in Materials Science and Engineering. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1121327
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1121327