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Neural Network Method Based on Concrete Carbonation Depth Prediction
| Content Provider | Scilit |
|---|---|
| Author | Wu, Duo Liu, Yuanrong Yin, Yuxue Deng, Zhiyong Liu, Zhifu |
| Copyright Year | 2021 |
| Description | Journal: Iop Conference Series: Earth and Environmental Science Carbonation is a typical disease that affects the long-term durability of concrete. In this paper, neural network toolbox in MATLAB software was employed to analyze sample parameters such as CO2 concentration, compressive strength, age and water-cement ratio in concrete carbonation research, and to predict the depth of carbonation. The results show that under the premise of setting reasonable parameters, the sample training results are satisfactory, the average error is about 7%∼14%, which basically meets the precision requirements of the preliminary identification of concrete carbonation depth. |
| Related Links | https://iopscience.iop.org/article/10.1088/1755-1315/825/1/012020/pdf |
| ISSN | 17551307 |
| e-ISSN | 17551315 |
| DOI | 10.1088/1755-1315/825/1/012020 |
| Journal | Iop Conference Series: Earth and Environmental Science |
| Issue Number | 1 |
| Volume Number | 825 |
| Language | English |
| Publisher | IOP Publishing |
| Publisher Date | 2021-07-01 |
| Access Restriction | Open |
| Subject Keyword | Journal: Iop Conference Series: Earth and Environmental Science Concrete Carbonation Carbonation Depth Prediction |
| Content Type | Text |
| Resource Type | Article |
| Subject | Earth and Planetary Sciences Physics and Astronomy Environmental Science |
