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Predicting Carbonation Depth of Prestressed Concrete under Different Stress States Using Artificial Neural Network
Joint Authors
Source
Advances in Artificial Neural Systems
Issue
Vol. 2009, Issue 2009 (31 Dec. 2009), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2010-02-22
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
Two artificial neural networks (ANN), back-propagation neural network (BPNN) and the radial basis function neural network (RBFNN), are proposed to predict the carbonation depth of prestressed concrete.
In order to generate the training and testing data for the ANNs, an accelerated carbonation experiment was carried out, and the influence of stress level of concrete on carbonation process was taken into account especially.
Then, based on the experimental results, the BPNN and RBFNN models which all take the stress level of concrete, water-cement ratio, cement-fine aggregate, cement-coarse aggregate ratio and testing age as input parameters were built and all the training and testing work was performed in MATLAB.
It can be found that the two ANN models seem to have a high prediction and generalization capability in evaluation of carbonation depth, and the largest absolute percentage errors of BPNN and RBFNN are 10.88% and 8.46%, respectively.
The RBFNN model shows a better prediction precision in comparison to BPNN model.
American Psychological Association (APA)
Lu, Chunhua& Liu, Ronggui. 2010. Predicting Carbonation Depth of Prestressed Concrete under Different Stress States Using Artificial Neural Network. Advances in Artificial Neural Systems،Vol. 2009, no. 2009, pp.1-8.
https://search.emarefa.net/detail/BIM-453391
Modern Language Association (MLA)
Lu, Chunhua& Liu, Ronggui. Predicting Carbonation Depth of Prestressed Concrete under Different Stress States Using Artificial Neural Network. Advances in Artificial Neural Systems No. 2009 (2009), pp.1-8.
https://search.emarefa.net/detail/BIM-453391
American Medical Association (AMA)
Lu, Chunhua& Liu, Ronggui. Predicting Carbonation Depth of Prestressed Concrete under Different Stress States Using Artificial Neural Network. Advances in Artificial Neural Systems. 2010. Vol. 2009, no. 2009, pp.1-8.
https://search.emarefa.net/detail/BIM-453391
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-453391