| Issue |
E3S Web Conf.
Volume 165, 2020
2020 2nd International Conference on Civil Architecture and Energy Science (CAES 2020)
|
|
|---|---|---|
| Article Number | 03034 | |
| Number of page(s) | 4 | |
| Section | Geology, Mapping, and Remote Sensing | |
| DOI | https://doi.org/10.1051/e3sconf/202016503034 | |
| Published online | 01 May 2020 | |
Prediction of Shear Characteristics of Unsaturated Soil Based on BP Neural Network
1 Department of Civil Engineering, Yanbian University, Yanji, 133002, China
2 Department of Civil Engineering, Kyungpook National University, Daegu, South Korea
* Corresponding author: grjin@ybu.edu.cn
The prediction model of shear strength parameters of unsaturated soil based on indoor test data is established by using BP neural network. Five kinds of network models with different number of hidden layer nodes are trained and studied, and the best network model is selected to conduct the prediction. The results show that the optimal BP network model is a single hidden layer structure of 8-16-2. Using this model to predict, the correlation coefficient and regression coefficient between the predicted value and the measured value are high, and the predicted result is reliable, so the method has certain practicability.
© The Authors, published by EDP Sciences, 2020
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